System

Abstract

To provide a system.SOLUTION: The system includes: means equipped in a terminal for a user, the means specifying the mental health or a reason for stress of the user through a conversation between an artificial intelligence character which checks stress on a regular basis and the user; means for notifying a parent of the user of the result or giving advice to a parent of the user; means for collecting data including utterances, expressions, or tones of the user; means including an emotional engine for analyzing the collected data; and means for specifying a reason of stress of the user on the basis of the result of analysis of the emotion engine.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] The number of children not attending school is on the rise, and there is a problem that even parents have difficulty understanding the stress their children are experiencing. [Means for solving the problem]

[0005] To solve this problem, we provide a system that equips children's devices with a conversational AI character and conducts regular stress checks. This system uses AI to identify the child's mental health and stress factors through conversations with the child, and notifies the parents of the results and gives advice. Furthermore, the AI ​​character analyzes the child's emotional state, identifies the stress factors, and provides corresponding advice. [Brief explanation of the drawings]

[0006] [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. 2 is a sequence diagram showing a flow of processing in the data processing system according to the first embodiment of the first form example. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Embodiment 1. [Figure 13] FIG. 10 is a sequence diagram showing a processing flow of a data processing system in a second embodiment of the second form example. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Embodiment Example 2. [Figure 15] FIG. 10 is a sequence diagram showing the flow of processing in a data processing system according to a third embodiment of the third embodiment. [Figure 16]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Embodiment 3. [Figure 17] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Form Example 1 when an emotion engine is combined. [Figure 19] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the second embodiment of the second form example when an emotion engine is combined. [Figure 20] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Form Example 2 when an emotion engine is combined. [Figure 21] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the third embodiment of the third form example when an emotion engine is combined. [Figure 22] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Form Example 3 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0007] 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.

[0008] First, the terms used in the following description will be explained.

[0009] 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, the 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), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

[0010] 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.

[0011] 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.

[0012] 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.

[0013] 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."

[0014] [First embodiment]

[0015] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0016] 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.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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.

[0022] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0023] 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.

[0024] 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.

[0025] 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.

[0026] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0027] "Example 1"

[0028] In one embodiment of the present invention, an AI character installed on a device for children conducts stress checks through conversations with the child. The AI ​​character identifies mental health conditions and stress factors from the child's comments and reactions. For example, if a child avoids talking about school, the AI ​​character can identify school-related stress.

[0029] "Example 2"

[0030] The AI ​​character then notifies the parent of the results and offers advice. The notification is sent to the parent's smartphone using the device's notification function. The advice provides specific solutions to issues that are causing stress to the child. For example, if a child is having trouble with friends at school, the AI ​​character will suggest that the parent try to talk to the child or seek professional help.

[0031] "Example 3"

[0032] The AI ​​character also analyzes the child's emotional state based on the content, tone, and facial expressions of the child's speech. For example, if the child expresses anger or sadness, the AI ​​character analyzes this information and identifies the cause of stress.

[0033] The processing flow of each embodiment will be described below.

[0034] "Example 1"

[0035] Step 1: The AI ​​character initiates a conversation with the child. This conversation can be initiated by the child interacting with the device, or by the AI ​​character periodically prompting the conversation.

[0036] Step 2: The AI ​​character will engage in conversation to explore the child's mental health and stressors, collecting information through questions such as, "How was your day?" and "Did anything interesting happen at school?"

[0037] Step 3: The AI ​​character analyzes the collected information and assesses the child's stress level, using AI natural language processing and machine learning techniques.

[0038] "Example 2"

[0039] Step 1: The AI ​​character notifies the parent of the analysis results. This notification is sent via the device's notification function directly to the parent's smartphone.

[0040] Step 2: The notification will include the child's stress level, its contributing factors, and recommendations. The recommendations will provide specific action plans to reduce the child's stress.

[0041] "Example 3"

[0042] Step 1: The AI ​​character analyzes the child's emotional state based on the content, tone, and facial expressions of the child's speech.

[0043] Step 2: The AI ​​character uses the emotional state analysis results to identify the child's stressors. For example, if the child expresses anger or sadness, the AI ​​character analyzes that information and identifies the stressors.

[0044] Step 3: Based on the identified stressors, the AI ​​character generates advice for the child and parent, providing specific courses of action to reduce the stressors.

[0045] Example 1

[0046] Next, a description will be given of Example 1 of Form 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."

[0047] Today's children are often exposed to stress at school and at home, making it important to properly understand their mental health. However, it is difficult for parents and teachers to accurately understand a child's stress and emotional state, which can delay appropriate responses. Furthermore, children often have difficulty expressing their own stress and emotions effectively. This has led to a need for effective methods to properly manage children's mental health.

[0048] The identification process by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. In this invention, the server is installed in a terminal for children and includes an AI character that performs regular stress checks, a means for identifying the child's mental health state and stress factors through conversation with the child, a means for notifying the results and providing advice to the parent, a means for collecting the child's comments and sending them to the generative AI model, and a means for receiving the analysis results from the generative AI model and providing appropriate feedback and advice to the child. This makes it possible to grasp the child's mental health state in real time and take appropriate measures quickly.

[0049] A "child-directed device" is an electronic device designed for use by children.

[0050] "Regular stress checks" are the process of assessing a child's stress level at regular intervals.

[0051] An "artificial intelligence character" is a virtual character that interacts with children using artificial intelligence technology.

[0052] "Conversation with a child" refers to the act of a child communicating with an AI character through voice or text.

[0053] "Mental health" refers to a child's mental stability and emotional state.

[0054] "Stressors" refer to causes or situations that cause stress to children.

[0055] "Notifying parents of results" refers to the act of communicating information about a child's mental health and stress factors to parents.

[0056] "Advice tools" are methods for providing appropriate advice and instruction to children and parents.

[0057] "Means of collecting statements" refers to methods for recording children's statements and saving them as data.

[0058] A "generative artificial intelligence model" is a model generated using artificial intelligence technology that performs natural language processing and sentiment analysis.

[0059] "Means for receiving analysis results" refers to a method for importing analysis results from a generative artificial intelligence model into a terminal.

[0060] "Means for providing appropriate feedback and advice" refers to methods for providing appropriate responses and advice to children based on the analysis results.

[0061] MODE FOR CARRYING OUT THE INVENTION

[0062] This invention is a system that uses an AI character installed on a device for children to identify a child's mental health condition and stress factors, and notifies the parents of the results and provides advice. A specific embodiment of this system is described below.

[0063] Generating a Program

[0064] The server generates the AI ​​character program to be installed on the device for children. This program uses natural language processing technology to analyze conversations with children and identify their mental health status and stress factors. Specifically, the program is developed using programming languages ​​such as Python and Java (registered trademark), and distributed to the device via AWS (registered trademark) (Amazon Web Services) or Google (registered trademark) Cloud Platform.

[0065] Program processing

[0066] The terminal installs the distributed program and starts the AI ​​character. The user (child) operates the terminal and starts a conversation with the AI ​​character. For example, if the user says "Hello," the AI ​​character will reply, "Hello, how was your day?"

[0067] The device uses a microphone to collect the user's speech. The collected voice data is converted into text in real time and sent to the generative AI model. For example, if a user says, "Nothing fun happened at school today," the text data is sent to the generative AI model.

[0068] The generative AI model analyzes the text data sent. Specifically, it uses generative AI models such as Google's Dialogflow or OpenAI's GPT-3 (registered trademark) to identify emotions and stress factors from the user's speech. The analysis results indicate that the user is likely to have negative feelings toward school.

[0069] The device receives the analysis results from the generative AI model. For example, if the device determines that the user has negative feelings about school, it uses voice synthesis technology to provide feedback to the user, such as, "Have you had any problems at school?"

[0070] Examples and prompts

[0071] As a concrete example, the following conversation can be considered:

[0072] User (child): "Nothing fun happened at school today."

[0073] AI character: "Oh yeah. Did you get in trouble at school?"

[0074] From this conversation, the AI ​​character identifies the possibility that the child has negative feelings about school.

[0075] Examples of prompts to be input to a generative AI model include:

[0076] Prompt: "What stressors might be causing your child to avoid talking about school?"

[0077] By inputting this prompt into the generative AI model, the AI ​​character can generate appropriate feedback and advice.

[0078] As described above, this invention is a system that makes it possible to grasp a child's mental health condition in real time and to take appropriate measures quickly.

[0079] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0080] Step 1:

[0081] The server generates programs for AI characters to be installed on children's devices and distributes them to the devices. Specifically, the server develops programs using programming languages ​​such as Python and Java and distributes them to devices via AWS or Google Cloud Platform. The input is the program source code, and the output is a program that can be installed on the device.

[0082] Step 2:

[0083] The terminal installs the distributed program and starts the AI ​​character. The user (child) operates the terminal and starts a conversation with the AI ​​character. Specifically, when the user says "Hello," the AI ​​character replies "Hello, how was your day?" The input is the user's voice, and the output is the AI ​​character's response.

[0084] Step 3:

[0085] The device uses a microphone to collect user speech and converts it into text in real time. The collected speech data is then converted into text using speech recognition technology. The input is the user's speech data, and the output is text data.

[0086] Step 4:

[0087] The device sends the generated text data to the generative AI model. Specifically, the device sends the text data to the generative AI model on the server via the Internet. The input is the text data, and the output is the data sent to the generative AI model.

[0088] Step 5:

[0089] The generative AI model analyzes the submitted text data and identifies mental health conditions and stress factors. Specifically, the generative AI model uses natural language processing technology to analyze the text data and identify emotions and stress factors. The input is the text data, and the output is the analysis results.

[0090] Step 6:

[0091] The device receives the analysis results from the generative AI model and provides appropriate feedback and advice to the user. Specifically, the device uses voice synthesis technology to provide feedback to the user based on the analysis results. For example, if it is determined that the user has negative feelings toward school, the device will provide feedback such as, "Have you had any trouble at school?" The input is the analysis results, and the output is feedback generated for the user.

[0092] Step 7:

[0093] The device notifies the parent of the analysis results and feedback. Specifically, the device sends notifications via the Internet to the parent's smartphone or email address. The inputs are the analysis results and feedback, and the output is a notification to the parent.

[0094] (Application example 1)

[0095] Next, a description will be given of Application Example 1 of Embodiment 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."

[0096] Today's children often experience stress due to various factors, including school and home environments. However, it is difficult for children themselves to recognize this stress and deal with it appropriately. It is also not easy for parents and educators to understand a child's stress level and respond early. Therefore, there is a need for a system that regularly checks children's mental health, identifies stress factors, and provides appropriate advice.

[0097] 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.

[0098] In this invention, the server is installed in a device for children and includes an AI character that performs regular stress checks, means for identifying the child's mental health condition and stress factors through conversation with the child, means for notifying the parents of the results and providing advice, means for using a generative AI model to evaluate the stress level from the child's comments and reactions, means for notifying the parents or experts when the stress level is high, and means for providing regular reports on the child's mental health condition, which makes it possible to detect a child's stress state early and take appropriate measures.

[0099] A "child-directed device" is an electronic device designed for use by children.

[0100] "Regular stress checks" are the process of assessing a child's stress level at regular intervals.

[0101] An "AI character" is a virtual character equipped with artificial intelligence that has the ability to collect and analyze information through dialogue with children.

[0102] "Conversation with a child" refers to the act of exchanging information between a child and an AI character through voice or text.

[0103] "Mental health" refers to a child's mental and emotional stability.

[0104] "Stressors" refer to causes or situations that cause stress to children.

[0105] "Means of notifying parents of results and providing advice" refers to methods for conveying information about their child's stress level and mental health status to parents and encouraging them to take appropriate measures.

[0106] The "generative AI model that assesses stress levels from children's statements and reactions" is an artificial intelligence model that analyzes children's behavior and words and determines the level of stress.

[0107] "Means to notify parents and professionals when stress levels are high" refers to a method to communicate this information to parents and professionals when a child's stress level exceeds a certain threshold.

[0108] "Means for providing regular reports on children's mental health status" refers to a method for regularly compiling information on children's mental health status and reporting it to parents and professionals.

[0109] The system for carrying out this invention is mainly composed of an AI character installed on a device for children. A specific embodiment of this system will be described below.

[0110] System configuration

[0111] The system consists of the following main components:

[0112] 1. Child-directed devices: Electronic devices such as smartphones and tablets used by children.

[0113] 2. AI Character: A virtual character equipped with artificial intelligence that collects and analyzes information through dialogue with children.

[0114] 3. Generative AI model: An artificial intelligence model for assessing stress levels from children's statements and reactions.

[0115] 4. Notification system: A system to notify parents and professionals when stress levels are high.

[0116] 5. Reporting system: A system that provides regular reports on children's mental health status.

[0117] Program processing

[0118] The server does the following:

[0119] 1. Conversation collection: Collect conversations between a child and an AI character in text format. For example, a child might answer "Hmm, nothing in particular" to the question "What did you do at school today?"

[0120] 2. Stress Level Analysis: Using a generative AI model, we assess stress levels from collected conversations. We use OpenAI's API to analyze conversations and determine the level of stress.

[0121] 3. Notification: Notify parents or professionals when stress levels are high, for example, by sending a message saying "Warning: Child's stress level is high."

[0122] 4. Generate reports: Regularly summarize the child's mental health status and provide it as a report to parents and professionals.

[0123] Hardware and software used

[0124] Hardware: smartphones, tablets, servers

[0125] Software: OpenAI API, generative AI models

[0126] Specific examples

[0127] Below are some examples of specific conversations and prompts:

[0128] Example conversation

[0129] AI: What did you do at school today?

[0130] Child: Hmm, nothing in particular.

[0131] AI: Did you hang out with friends?

[0132] Child: No, not really.

[0133] Prompt Sentence Examples

[0134] Assess your child's stress level from the following conversation:

[0135] AI: What did you do at school today?

[0136] Child: Hmm, nothing in particular.

[0137] AI: Did you hang out with friends?

[0138] Child: No, not really.

[0139] evaluation:

[0140] In this way, the system can detect stress in children early and take appropriate measures.

[0141] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0142] Step 1:

[0143] Conversation collection

[0144] The device collects conversations between the child and the AI ​​character in text format. Specifically, when the child speaks to the device, the speech is converted into text and saved as a conversation log. The input is the child's speech, and the output is a text-format conversation log.

[0145] Step 2:

[0146] Stress level analysis

[0147] The server inputs the collected conversation logs into a generative AI model to evaluate stress levels. Specifically, it uses OpenAI's API to analyze the conversation content and determine the degree of stress. The input is a text-format conversation log, and the output is an evaluation result of the stress level.

[0148] Step 3:

[0149] notification

[0150] If the stress level is high, the server notifies the parent or expert. Specifically, based on the stress level assessment result, it sends a message to the parent or expert saying, "Warning: Your child's stress level is high." The input is the stress level assessment result, and the output is the notification message.

[0151] Step 4:

[0152] Generate reports

[0153] The server periodically summarizes the child's mental health status and provides it to parents and specialists as a report. Specifically, it aggregates conversation logs and stress level assessment results over a certain period of time and generates a report. The input is the conversation logs and stress level assessment results over a certain period of time, and the output is a mental health status report.

[0154] Step 5:

[0155] Providing advice

[0156] The server identifies the causes of stress and provides corresponding advice. Specifically, it uses a generative AI model to analyze the causes of stress and generate appropriate advice. The input is the conversation log and the stress level assessment results, and the output is the content of the advice.

[0157] Example 2

[0158] Next, a description will be given of Example 2 of Form 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."

[0159] Today's children are often exposed to stress at school and at home, and it is necessary to detect this stress early and deal with it appropriately. However, it is difficult for parents to accurately grasp their children's stress levels and provide appropriate advice. With conventional methods, there is a lack of a system in place to identify the causes of children's stress and notify parents, making it difficult to protect children's mental health.

[0160] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for transmitting generated data to a cloud server, a means for the cloud server to analyze the stress level using the generated AI model, and a means for the cloud server to generate notification content and advice based on the analysis result. This makes it possible to detect stress in children early and provide appropriate advice to parents.

[0161] The "artificial intelligence character" is a program that is installed on devices for children, conducts regular stress checks, and identifies mental health conditions and stress factors through conversations with children.

[0162] The "cloud server" is a remote server that receives data via the internet, analyzes stress levels using a generative AI model, and generates notifications and advice based on the analysis results.

[0163] A "generative AI model" is an artificial intelligence algorithm that analyzes the received data and assesses a child's stress level.

[0164] The "notification function" is a function that enables the terminal to send notification of results and advice to the parent's information terminal.

[0165] A "stress check" is a process of collecting data on a child's behavior and emotions to assess the presence and level of stress.

[0166] "Analysis results" are information about stress levels and factors that the generative AI model outputs based on input data.

[0167] "Advice" refers to specific solutions or suggestions provided to parents based on the analysis results.

[0168] "Data transmission means" refers to the functions and protocols for transmitting data from the terminal to the cloud server.

[0169] This invention is a system that uses an AI character installed on a device for children to periodically check a child's stress level, notify the parents of the results, and provide appropriate advice. This system is implemented using the following hardware and software.

[0170] Hardware and software used

[0171] Hardware: Smartphones, cloud servers

[0172] Software: Generative AI model, notification function (depending on smartphone OS)

[0173] Specific operation of the system

[0174] 1. The user enters data to measure the child's stress level.

[0175] Users open a smartphone app and answer questions about their child's behavior and emotions.

[0176] Example: A user fills out an app's questionnaire form and responds to the prompt, "Tell us about any recent changes in your child's behavior or emotions" by typing, "He recently had a fight with a friend at school."

[0177] 2. The device sends the entered data to the cloud server.

[0178] When the smartphone app presses the "send" button, the data is uploaded to a cloud server via the Internet.

[0179] 3. The server inputs the received data into a generative AI model to analyze stress levels.

[0180] The server passes the data to a generative AI model implemented in Python, which determines the stress level as "high" based on the information that the user "had a fight with a friend."

[0181] 4. Based on the analysis results, the server identifies the child's stress factors and generates notifications and advice for parents.

[0182] The server generates a message saying, "Your child is having trouble with friendships at school. We suggest you try to communicate with them or seek professional help."

[0183] 5. The server generates notifications and sends advice to the device.

[0184] The server generates a message and sends it to a smartphone app, which receives the message.

[0185] 6. The device uses the notification function to send a notification to the parent's smartphone.

[0186] A notification will appear in the notification bar on your smartphone saying, "We have an important message for you regarding stress in children."

[0187] Prompt Sentence Examples

[0188] "Tell me what problems your child has been having at school recently."

[0189] "Tell me about any recent changes in your child's behavior or emotions."

[0190] This system will enable parents to detect stress in their children early and provide appropriate coping strategies, thereby strengthening support for protecting children's mental health.

[0191] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0192] Step 1:

[0193] The user inputs data to measure the child's stress level.

[0194] Input: A user opens a smartphone app and answers questions about their child's behavior and emotions.

[0195] What happens: A user fills out an app questionnaire prompting them to "Tell us about any recent changes in your child's behavior or emotions," and answers, "They recently had a fight with a friend at school."

[0196] Output: The input data is saved in the smartphone app.

[0197] Step 2:

[0198] The terminal transmits the input data to the cloud server.

[0199] Input: User input data stored in the smartphone app.

[0200] Specific operation: When the smartphone app presses the "send" button, the data is uploaded to a cloud server via the Internet.

[0201] Output: Data is sent to the cloud server.

[0202] Step 3:

[0203] The server inputs the received data into a generative AI model to analyze stress levels.

[0204] Input: User input data sent to the cloud server.

[0205] Specific operation: The server passes data to a generative AI model implemented in Python, which determines the stress level as "high" based on the information that "you had a fight with a friend."

[0206] Output: Stress level analysis results are generated.

[0207] Step 4:

[0208] Based on the analysis results, the server identifies the child's stress factors and generates notifications and advice to be sent to parents.

[0209] Input: Stress level analysis results from a generative AI model.

[0210] Specific behavior: The server generates a message saying, "Your child is having trouble with friendships at school. We suggest you try to communicate with them or seek professional help."

[0211] Output: Notifications and advice are generated.

[0212] Step 5:

[0213] The server generates notifications and advice and sends them to the terminal.

[0214] Input: Generated notification content and advice.

[0215] Specific operation: The server generates a message and sends it to the smartphone app, which then receives the message.

[0216] Output: Notifications and advice are sent to the smartphone app.

[0217] Step 6:

[0218] The device uses the notification function to send a notification to the parent's smartphone.

[0219] Input: Notifications and advice sent by the server.

[0220] What it does: A notification will appear in your smartphone's notification bar saying, "We have an important message for you about your child's stress."

[0221] Output: A notification will appear on the parent's smartphone.

[0222] (Application example 2)

[0223] Next, a description will be given of Application Example 2 of Form 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."

[0224] Today's children often experience stress due to various factors, including school, home, and friendships. However, children themselves are often unable to express their stress appropriately, making it difficult for parents to understand the situation. It is also difficult for parents to understand their children's stressors and find appropriate ways to deal with them. This puts children at risk of developing poor mental health. This invention aims to protect children's mental health by identifying their stressors and providing appropriate advice to parents.

[0225] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server is installed in a terminal for children and includes an AI character that performs regular stress checks, means for identifying the child's mental health condition and stress factors through conversation with the child, means for notifying the results and providing advice to the parent, means for identifying the child's stress factors using a generative AI model, means for generating specific advice for the identified stress factors, and means for sending a notification to the parent's terminal. This makes it possible to quickly and accurately identify the child's stress factors and provide appropriate advice to the parent.

[0226] A "child-directed device" is an electronic device designed for use by children.

[0227] "Regular stress checks" are the process of assessing a child's stress levels at regular intervals.

[0228] An "artificial intelligence character" is a virtual character that uses AI technology to interact with children and analyze their emotions and stress.

[0229] "Children's mental health" refers to a child's mental health and emotional stability.

[0230] "Stressors" refer to the causes and situations that cause children to feel stressed.

[0231] "Means of notifying parents of results and giving advice" refers to methods and functions for informing parents of their child's stress level and how to deal with it.

[0232] A "generative AI model" is a model that has been trained using artificial intelligence to perform a specific task.

[0233] "Specific advice for identified stressors" refers to specific coping strategies or suggestions provided based on the detected causes of stress.

[0234] "Means for sending notifications to parent's terminal" refers to a method or function for sending information to the electronic device used by the parent.

[0235] The system for implementing this invention is composed of a terminal for children, a server, and a terminal for parents. Each component and its function will be explained below.

[0236] Children's devices

[0237] The device for children is equipped with an AI character that periodically converses with the child to identify their mental health and stressors. The content of the conversation is converted into text data using voice recognition technology and sent to a server.

[0238] server

[0239] The server uses a generative AI model to identify the child's stressors, using prompts such as the following to input the AI ​​model:

[0240] 1. Identifying stressors:

[0241] Identify stressors if your child is struggling with: Having trouble with friendships at school.

[0242] 2. Providing advice:

[0243] What advice should you offer parents if their child is struggling with friendships at school?

[0244] The server inputs these prompts into a generative AI model and uses the results to identify the child's stressors. It then generates specific advice for each identified stressor.

[0245] Parent's device

[0246] The parent's device will receive a notification sent from the server, which will include information about the child's stressors and specific advice on how to address them, allowing the parent to take appropriate measures to support their child's mental health.

[0247] Hardware and software used

[0248] Children's devices: smartphones, tablets, smart speakers, etc.

[0249] Server: Cloud server (e.g. AWS, Google Cloud)

[0250] Parent's device: smartphone, tablet, PC, etc.

[0251] Software: Python, OpenAI API, SMTP server (e.g. Gmail SMTP)

[0252] Specific examples

[0253] For example, if a child says to the device, "I'm having trouble with friends at school," the process will proceed as follows:

[0254] 1. The child's device converts the voice into text data and sends it to the server.

[0255] 2. The server uses a generative AI model to identify the stressor and uses the following prompt:

[0256] Identify stressors if your child is struggling with: Having trouble with friendships at school.

[0257] 3. The server generates advice for the identified stressors and uses the following prompt:

[0258] What advice should you offer parents if their child is struggling with friendships at school?

[0259] 4. The server notifies the parent device of the results obtained.

[0260] In this way, it becomes possible to quickly and accurately identify stressors in children and provide appropriate advice to parents.

[0261] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0262] Step 1:

[0263] A device for children begins a dialogue with the child. The device uses voice recognition technology to convert what the child says into text data. The input is the child's voice, and the output is text data. This text data serves as the basis for identifying the child's mental health status and stress factors.

[0264] Step 2:

[0265] The terminal sends the converted text data to the server. The input is text data, and the output is data sent to the server. The server receives this data and proceeds to the next processing step.

[0266] Step 3:

[0267] The server uses a generative AI model to identify children's stressors from text data. The input is the text data, and the output is the stressor identification results. The server inputs the AI ​​model using the following prompt sentence:

[0268] Identify stressors if your child is experiencing: [Text data]

[0269] The generative AI model identifies stressors based on this prompt.

[0270] Step 4:

[0271] The server generates specific advice for the identified stressors. The input is the stressor identification result, and the output is the specific advice. The server inputs the following prompt to the AI ​​model:

[0272] What advice should you offer parents if their child is struggling with [stressor]?

[0273] The generative AI model generates specific advice based on this prompt.

[0274] Step 5:

[0275] The server notifies the parent device of the generated advice and the results of identifying stress factors. The input is the advice and the results of identifying stress factors, and the output is the notification to the parent device. The server uses an SMTP server to send the notification to the parent's email address.

[0276] Step 6:

[0277] The parent's device receives the notification and the parent checks the content. The input is the notification from the server, and the output is the information the parent checks. Based on this information, the parent can take appropriate measures to support their child's mental health.

[0278] In this way, it becomes possible to quickly and accurately identify stressors in children and provide appropriate advice to parents.

[0279] Example 3

[0280] Next, a description will be given of a third embodiment of the third embodiment. 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."

[0281] Previous stress check systems for children had the problem of being unable to accurately identify a child's emotional state and stress factors. Furthermore, they lacked the means to provide appropriate advice to parents, making it difficult to effectively manage their children's mental health.

[0282] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0283] In this invention, the server includes means for capturing the child's voice and video, means for converting the captured voice data into text, means for analyzing facial expressions from the video data, means for analyzing the text data and identifying the emotional state, and means for reporting the emotional state and its cause to the parent. This makes it possible to accurately identify the child's emotional state and stress factors and provide appropriate advice to the parent.

[0284] A "child-directed device" is an electronic device designed for use by children.

[0285] "Regular stress checks" are the process of assessing a child's stress levels at regular intervals.

[0286] An "artificial intelligence character" is a virtual character programmed to interact with children and analyze their emotions and stress levels.

[0287] "Children's mental health" refers to the state of a child's mental and emotional health.

[0288] "Stressors" refer to causes or situations that cause stress to children.

[0289] "Means of notifying parents of results and giving advice" refers to methods and functions for communicating analysis results to parents and proposing appropriate countermeasures.

[0290] "Means for capturing audio and video of children" refers to the ability to collect audio and video of children using a microphone and camera.

[0291] The "means for converting captured voice data into text" is a function that converts voice data into text data using voice recognition technology.

[0292] "Means for analyzing facial expressions from video data" refers to a function that uses video analysis technology to recognize a child's facial expressions and identify their emotional state.

[0293] The "means for analyzing text data and identifying an emotional state" is a function that uses natural language processing technology to analyze text data and determine a child's emotional state.

[0294] "Means for reporting emotional state and its causes to parents" refers to methods or functions for conveying the analysis results to parents and explaining the child's emotional state and its causes.

[0295] This invention is a system that uses an AI character installed on a device for children to identify a child's mental health condition and stress factors and notify the parents of the results. A specific embodiment of this system is described below.

[0296] First, the user (parent) prepares a device for the child to use. This device is equipped with a microphone and camera, and can capture the child's voice and video. The device captures the child's speech and facial expressions in real time and sends this data to the server.

[0297] The server converts the received audio data into text using Google Cloud Speech-to-Text. This process captures the child's speech as text data. The server then analyzes the child's facial expressions from the video data using Microsoft® Azure® Face API. This identifies the child's emotional state.

[0298] Additionally, the server uses OpenAI's GPT-3 to analyze the text data and IBM Watson® Tone Analyzer to identify the child's emotional state. This makes it clear what emotions the child is feeling. For example, if a child says, "I had a fight with a friend at school today," and displays an angry expression, the server will identify that the child is feeling angry.

[0299] Finally, the server reports the analysis results to the user (parent). For example, it may notify the parent that "your child is feeling angry because of a fight at school." This notification may also include appropriate advice. For example, it may provide specific advice such as "It is important to talk with your child and understand the cause of the fight."

[0300] As a concrete example, the following prompt sentence can be used:

[0301] Prompt: "Analyze audio and video recordings of a child talking about an incident at school and identify their emotional state. In particular, if they express anger or sadness, identify the cause of this."

[0302] In this way, the present invention can accurately identify the emotional state and stress factors of a child and provide appropriate advice to the parents. The flow of the identification process in the third embodiment will be described with reference to FIG.

[0303] Step 1:

[0304] The device captures audio and video of the child.

[0305] Specifically, the device uses a microphone and camera to record the child's voice and facial expressions in real time.

[0306] Input: Child's audio and video

[0307] Output: Captured audio and video data

[0308] Step 2:

[0309] The device sends the captured data to the server.

[0310] Specifically, the device transmits the captured audio and video data to the server using a secure communication protocol (e.g., HTTPS).

[0311] Input: Captured audio and video data

[0312] Output: Audio and video data sent to the server

[0313] Step 3:

[0314] The server converts the audio data into text.

[0315] Specifically, the server uses Google Cloud Speech-to-Text to convert the received voice data into text data.

[0316] Input: Audio data

[0317] Output: Text data

[0318] Step 4:

[0319] The server analyzes facial expressions from the video data.

[0320] Specifically, the server uses the Microsoft Azure Face API to analyze the child's facial expressions from the received video data and identify their emotional state.

[0321] Input: Video data

[0322] Output: Analyzed facial expression data

[0323] Step 5:

[0324] The server analyzes the text data to identify the emotional state.

[0325] Specifically, the server uses OpenAI's GPT-3 to analyze text data and IBM Watson Tone Analyzer to identify emotional states.

[0326] Input: Text data

[0327] Output: Identified emotional state

[0328] Step 6:

[0329] The server reports the emotional state and its cause to the user.

[0330] Specifically, the server notifies the user (parent) of the analysis results, explains the child's emotional state and its causes, and provides appropriate advice.

[0331] Input: Identified emotional state and its cause

[0332] Output: Analysis results and advice reported to the user

[0333] (Application example 3)

[0334] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[0335] Today's children are often exposed to stress and emotional fluctuations at home and school, which can result in poor mental health. However, it is difficult for parents and guardians to understand their children's emotional state and stressors in real time. Furthermore, if children are unable to express their emotions appropriately, problems may go unnoticed. This can delay appropriate measures to protect children's mental health.

[0336] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0337] In this invention, the server is installed in a device for children and includes an artificial intelligence character that performs regular stress checks, means for identifying the child's mental health condition and stress factors through conversation with the child, means for notifying the parents of the results and providing advice, means for analyzing the child's voice data and analyzing the emotional state, means for analyzing the child's video data and analyzing the emotional state from facial expressions, means for integrating the results of the emotion analysis of the voice data and video data and detecting abnormalities, and means for notifying the parents or guardians when an abnormality is detected. This makes it possible to grasp the child's emotional state and stress factors in real time, detect abnormalities early, and take appropriate action.

[0338] A "child-directed device" is an electronic device designed for use by children.

[0339] "Regular stress checks" are the process of assessing a child's stress levels at regular intervals.

[0340] An "artificial intelligence character" is a virtual character that uses AI technology to interact with children and analyze their emotions and stress.

[0341] "Conversation with a child" refers to the act of a child communicating with an AI character through voice or text.

[0342] "Mental health" refers to a child's mental and emotional stability and well-being.

[0343] "Stressors" refer to causes or situations that cause stress to children.

[0344] "Parent notification" refers to the act of informing parents or guardians of the results of the assessment of their child's emotional state and stress level.

[0345] "Advice tools" are ways of suggesting appropriate responses or actions to children and parents.

[0346] "Analyzing audio data" is the process of analyzing the content and tone of a child's speech to identify their emotional state.

[0347] "Means for analyzing emotional states" are techniques and methods for assessing a child's emotions from their voice and facial expressions.

[0348] "Analyzing video data" is the process of analyzing a child's facial expressions and movements to identify their emotional state.

[0349] "Means for analyzing emotional states from facial expressions" refers to techniques and methods that use video data to analyze children's facial expressions and evaluate their emotions.

[0350] "Sentiment analysis integration" refers to the process of combining the analysis results of audio data and video data to assess the overall emotional state.

[0351] "Anomaly detection methods" are techniques or methods for identifying unusual emotional states or stress levels.

[0352] "Means for notifying parents or guardians" refers to the method by which information about an abnormality is notified to parents or guardians when it is detected.

[0353] The system for implementing this invention is installed in a device for children. The device includes an AI character that performs regular stress checks and identifies mental health conditions and stress factors through conversations with the child. It also has a function to notify parents of the results and provide advice.

[0354] Hardware and software used

[0355] Hardware: smartphone, tablet, camera, microphone

[0356] Software: Python, OpenCV, TENSORFLOW (registered trademark), Transformers (Hugging Face emotion analysis model), DeepFace

[0357] Data processing and calculation

[0358] 1. Voice data analysis: The device's microphone is used to collect the child's voice, and a speech recognition model (Transformers) is used to analyze the child's emotional state. The voice data is converted into text and sentiment analysis is performed.

[0359] 2. Video Data Analysis: We collect video data of children using the device camera and analyze their emotional state from facial expressions using OpenCV and DeepFace. The video data is analyzed frame by frame, and emotions are identified from facial expressions.

[0360] 3. Sentiment Analysis Integration: The sentiment analysis results of audio and video data are integrated to evaluate the overall emotional state. If an anomaly is detected, a notification will be sent to parents or guardians.

[0361] Specific examples

[0362] For example, if a child says "I'm scared," and the speech recognition model detects "fear" and the facial expression recognition model also detects "fear," the system will detect an anomaly and send a notification to the parent, including the cause of the child's fear and advice on what the parent should do.

[0363] Prompt Sentence Examples

[0364] Please enter your child's voice data.

[0365] "Please enter your child's video data."

[0366] In this way, it is possible to grasp a child's emotional state and stress factors in real time, detect abnormalities early, and take appropriate action.

[0367] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0368] Step 1:

[0369] The device collects the child's voice data through a microphone. The input is the child's voice, and the output is a voice data file. This voice data is saved for subsequent voice recognition processing.

[0370] Step 2:

[0371] The device inputs the collected voice data into a voice recognition model (Transformers) and converts it into text data. The input is a voice data file, and the output is text data. This text data is used for sentiment analysis.

[0372] Step 3:

[0373] The device inputs the converted text data into a sentiment analysis model to identify the emotional state. The input is the text data, and the output is the emotional state (e.g., joy, sadness, fear, etc.). This emotional state is used in subsequent processing.

[0374] Step 4:

[0375] The device collects video data of the child through a camera. The input is the child's video, and the output is a video data file. This video data is saved for subsequent facial expression recognition processing.

[0376] Step 5:

[0377] The device inputs the collected video data into a facial expression recognition model (OpenCV and DeepFace) to identify the emotional state from the facial expressions. The input is a video data file, and the output is the emotional state (e.g., joy, sadness, fear, etc.). This emotional state is used in subsequent processing.

[0378] Step 6:

[0379] The terminal integrates the emotion analysis results of the audio data and the video data to evaluate the overall emotional state. The input is the emotional state of the audio data and the emotional state of the video data, and the output is the integrated emotional state. This integrated emotional state is used for anomaly detection.

[0380] Step 7:

[0381] The device detects anomalies based on the integrated emotional state. The input is the integrated emotional state, and the output is the anomaly detection result. If an anomaly is detected, a notification is sent to the parent or guardian.

[0382] Step 8:

[0383] The device sends a notification to parents or guardians when an abnormality is detected. The input is the anomaly detection result, and the output is a notification message. This notification message includes the child's emotional state, stress factors, and advice on what the parent should do.

[0384] 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.

[0385] "Example 1"

[0386] One embodiment of the present invention is a system that includes an emotion engine in which an AI character recognizes a child's emotions. This emotion engine analyzes the child's emotional state based on the child's words, facial expressions, tone of voice, and so on. For example, if a child says, "Today was fun," the emotion engine determines from that statement that the child is feeling joy. Similarly, if a child cries and says, "I can't take it anymore," the emotion engine determines from that statement and the crying that the child is feeling sadness or anger.

[0387] "Example 2"

[0388] Furthermore, the emotion engine adjusts the AI ​​character's response according to the child's emotional state. For example, if the AI ​​character determines that the child is feeling happy, it will offer pleasant conversations to the child. On the other hand, if the AI ​​character determines that the child is feeling sad or angry, it will respond empathetically to the child. This allows the AI ​​character to engage in dialogue that is adapted to the child's emotional state.

[0389] "Example 3"

[0390] The emotion engine also notifies parents of their child's emotional state. For example, if the emotion engine determines that a child is feeling sad or angry, it notifies the parent of that information. This allows parents to understand their child's emotional state and take appropriate action.

[0391] The processing flow of each embodiment will be described below.

[0392] "Example 1"

[0393] Step 1: The AI ​​character initiates a dialogue with the child.

[0394] Step 2: The emotion engine analyzes the child's emotional state based on their words, facial expressions, tone of voice, etc.

[0395] Step 3: The emotion engine communicates the analysis results to the AI ​​character.

[0396] "Example 2"

[0397] Step 1: The emotion engine determines the child's emotional state.

[0398] Step 2: The emotion engine issues instructions to adjust the AI ​​character's response based on the judgment results.

[0399] Step 3: The AI ​​character adjusts its dialogue to the child according to the instructions.

[0400] "Example 3"

[0401] Step 1: The emotion engine determines the child's emotional state.

[0402] Step 2: The emotion engine notifies the parent about the child's emotional state.

[0403] Step 3: Parents receive notifications and are aware of their child's emotional state.

[0404] Example 1

[0405] Next, a description will be given of Example 1 of Form 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."

[0406] Today's children often experience stress in various environments, such as at school and at home. However, it is difficult for children themselves to recognize this stress and deal with it appropriately. It is also difficult for parents and educators to accurately understand a child's stress level and take appropriate measures. Therefore, there is a need for a system that regularly checks children's mental health, identifies the causes of stress, and provides appropriate advice.

[0407] 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.

[0408] In this invention, the server is installed in a device for children and includes an artificial intelligence character that performs regular stress checks, means for identifying the child's mental health condition and stress factors through conversation with the child, means for notifying the parents of the results and providing advice, means for collecting data such as the child's comments, facial expressions, and tone of voice, means including an emotion engine for analyzing the collected data, and means for identifying the child's stress factors based on the analysis results. This makes it possible to accurately grasp the child's mental health condition and take appropriate measures.

[0409] A "child-directed device" is an electronic device designed for use by children.

[0410] "Regular stress checks" are the process of assessing a child's stress level at regular intervals.

[0411] An "artificial intelligence character" is a virtual character that interacts with children using artificial intelligence technology.

[0412] "Children's mental health" refers to the state of a child's mental and emotional health.

[0413] "Stressors" refer to the causes and situations that cause children to feel stressed.

[0414] "Means of notifying parents of results and giving advice" refers to the function of informing parents of the results of their child's stress state and suggesting appropriate ways to respond.

[0415] "Means for collecting data such as a child's statements, facial expressions, and tone of voice" refers to functions for obtaining information such as a child's words, facial expressions, and tone of voice.

[0416] An "emotion engine" is software or algorithms that analyze collected data and determine a child's emotional state.

[0417] "Means for identifying children's stress factors based on analysis results" refers to a function that uses the analysis results of the emotion engine to identify the specific causes of stress in children.

[0418] MODE FOR CARRYING OUT THE INVENTION

[0419] This invention is a system that uses an AI character installed on a device for children to check a child's mental health and identify the causes of stress. A specific embodiment of this system will be described below.

[0420] System configuration

[0421] The system consists of the following major components:

[0422] 1. Child-directed devices: Electronic devices designed for use by children, including hardware such as microphones, cameras, and speakers.

[0423] 2. Artificial Intelligence Character: A virtual character that interacts with children and uses natural language processing (NLP) technology to conduct conversations.

[0424] 3. Emotion engine: Software that analyzes data such as a child's speech, facial expressions, and tone of voice to determine their emotional state. Specifically, it uses Google Cloud Natural Language API and IBM Watson Tone Analyzer.

[0425] 4. Server: A central processing unit for analyzing the collected data and feeding back the results.

[0426] System Operation

[0427] The device initiates a conversation when the child speaks to the AI ​​character. For example, if the child says "Hello," the AI ​​character responds with "Hello, how was your day?" During this conversation, the device collects data such as the child's remarks, facial expressions, and tone of voice.

[0428] The collected data is sent from the device to a server. The server uses an emotion engine to analyze the data and determine the child's emotional state. For example, if a child says, "Today was fun," the emotion engine will determine from that statement that the child is feeling joy. If a child cries and says, "I can't take it anymore," the emotion engine will determine from that statement and the crying that the child is feeling sadness or anger.

[0429] The analysis results are fed back from the server to the device. The device then provides the feedback to the child through an AI character. For example, if the analysis result is "joy," the AI ​​character will respond, "You had fun today. What did you do?" If the analysis result is "sadness" or "anger," the AI ​​character will respond, "What's wrong? Did something happen?"

[0430] Furthermore, the server will identify the child's stressors based on the analysis results. For example, if a child avoids talking about school, it will determine that the child is experiencing school-related stress. This information will be notified to the parents, and appropriate advice will be provided.

[0431] Examples and prompts

[0432] Below are some specific examples and examples of prompts to input to the generative AI model.

[0433] Example 1: When a child says, "Today was fun," the device collects the statement and sends it to the server. The server's emotion engine analyzes it and determines that the child is feeling happy. The device responds through an AI character, "Today was fun, what did you do?"

[0434] Example 2: If a child cries and says, "I can't take it anymore," the device will collect the words and the crying and send them to the server. The server's emotion engine will analyze the data and determine that the child is feeling sad or angry. The device will respond through an AI character, asking, "What's wrong? Did something happen?"

[0435] Example prompt sentence:

[0436] "What stressors might be causing your child to avoid talking about school?"

[0437] "If a child says, 'I had fun today,' how does the emotion engine parse that?"

[0438] In this way, users can understand the operation of the system and utilize it appropriately.

[0439] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0440] Step 1:

[0441] The device starts a conversation by having the child speak to the AI ​​character. The user (child) might say, for example, "Hello." Based on this input, the device collects voice data, and the AI ​​character responds with, "Hello, how was your day?" In this step, voice data collection and an initial response are performed.

[0442] Step 2:

[0443] The device collects data such as the child's remarks, facial expressions, and tone of voice. Specifically, it records audio with a microphone and captures facial expressions with a camera. For example, if a child says, "Today was fun," the audio data and facial expression data are collected. In this step, audio data and video data are collected.

[0444] Step 3:

[0445] The device sends the collected data to the server. The data is encrypted and sent securely. For example, voice data and facial expression data are sent to the server. In this step, data is sent and encrypted.

[0446] Step 4:

[0447] The server analyzes the received data and uses an emotion engine to analyze the child's emotional state. Specifically, it uses software such as Google Cloud Natural Language API and IBM Watson Tone Analyzer. For example, it analyzes the voice data to determine whether the child is feeling "fun." In this step, data analysis and emotional state determination are performed.

[0448] Step 5:

[0449] The server feeds back the analysis results to the device. The device then provides feedback to the child through the AI ​​character. For example, if the analysis result is "joy," the AI ​​character responds, "You had fun today. What did you do?" In this step, the analysis results are fed back and a response is generated.

[0450] Step 6:

[0451] The server identifies the child's stressors based on the analysis results. For example, if a child avoids talking about school, it is determined that the child is experiencing stress related to school. This information is then notified to the parent, who can provide appropriate advice. In this step, the stressors are identified and notified to the parent.

[0452] (Application example 1)

[0453] Next, a description will be given of Application Example 1 of Embodiment 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."

[0454] In modern society, it is important to identify children's mental health conditions and stressors early and respond appropriately. However, it is difficult for parents and educators to accurately grasp children's emotional states and stressors, and these are often overlooked. Furthermore, children themselves are often unable to express their emotions and stress appropriately. This puts children at risk of developing poor mental health.

[0455] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server is installed in a device for children and includes an AI character that performs regular stress checks, means for identifying a child's mental health condition and stress factors through conversation with the child, means for notifying the parents of the results and providing advice, means including an emotion engine that recognizes the child's emotional state by analyzing the child's words, facial expressions, and tone of voice, and means for storing the child's emotional state and stress factors in a database and performing long-term analysis. This makes it possible to identify a child's mental health condition and stress factors early and take appropriate measures.

[0456] A "child-oriented device" is an electronic device designed for everyday use by children.

[0457] "Regular stress checks" are the process of assessing a child's stress level at regular intervals.

[0458] An "AI character" is a virtual character equipped with artificial intelligence that collects and analyzes information by interacting with children.

[0459] "Conversation with a child" refers to the act of a child communicating with an AI character through voice or text.

[0460] "Mental health" refers to a child's mental stability and sense of well-being.

[0461] A "stressor" is a cause or situation that causes stress to a child.

[0462] "Means of notifying parents of results and giving advice" refers to a function that informs parents of their child's mental health status and stress factors and suggests appropriate responses.

[0463] The "Emotion Engine" is an artificial intelligence technology that analyzes a child's words, facial expressions, and tone of voice to recognize their emotional state.

[0464] A "database" is a system for storing and managing information about a child's emotional state and stressors.

[0465] "Longitudinal analysis" is the process of using collected data to assess changes in children's mental health and stressors over time.

[0466] The system for implementing this invention is centered around an AI character installed on a device for children. The system identifies mental health conditions and stress factors through conversations with children, and has the function of notifying parents of the results and providing advice. It also uses an emotion engine to analyze the child's words, facial expressions, and tone of voice to recognize their emotional state.

[0467] Hardware and Software Configuration

[0468] Hardware: Children's devices such as smartphones, smart glasses, and head-mounted displays.

[0469] Software: Python, TensorFlow, database management system (e.g., MySQL®).

[0470] Data processing and calculation

[0471] 1. Data collection: The device collects conversation data (voice, text) with the child, facial expression data (camera), and tone of voice data (microphone).

[0472] 2. Data preprocessing: The collected data is converted into text data and then converted into numerical data using a tokenizer.

[0473] 3. Emotion Recognition: The emotion engine uses a Long Short-Term Memory (LSTM) network to analyze a child's speech, facial expressions, and tone of voice to recognize their emotional state.

[0474] 4. Identifying stressors: Identify stressors from the conversation and notify parents if necessary.

[0475] 5. Data storage and analysis: Children's emotional states and stress factors are stored in a database for long-term analysis.

[0476] Specific examples

[0477] For example, if a child says, "Today was fun," the emotion engine will judge the statement as "Positive." If a child says, "I can't take it anymore," while crying, the emotion engine will judge the statement and the crying as "Negative."

[0478] Prompt Sentence Examples

[0479] An example of a prompt to input to a generative AI model is as follows:

[0480] If your child says, "Today was fun," try to recognize the emotion in this statement.

[0481] This system will enable early identification of children's mental health conditions and stressors, allowing appropriate responses, enabling parents and educators to accurately understand their children's emotional state and provide the necessary support.

[0482] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0483] Step 1:

[0484] The device collects conversation data (voice, text), facial expression data (camera), and tone of voice data (microphone). The input is the child's words, facial expressions, and tone of voice, and the output is the collection of this data. Specifically, the device's microphone and camera are used to acquire data in real time.

[0485] Step 2:

[0486] The terminal converts the collected data into text data and then converts it into numerical data using a tokenizer. The input is voice data and text data, and the output is numerical data. Specifically, the terminal uses voice recognition software to convert voice into text, and then uses a tokenizer to convert the text into numerical data.

[0487] Step 3:

[0488] The server uses an emotion engine to analyze the numerical data and recognize the child's emotional state. The input is numerical data, and the output is the recognition result of the emotional state. Specifically, it analyzes the data using an LSTM (Long Short-Term Memory) network and determines the emotional state as "Positive" or "Negative."

[0489] Step 4:

[0490] The server identifies stress factors from the conversation content and notifies parents as necessary. The input is the recognition result of the emotional state and the conversation content, and the output is the identification and notification of stress factors. Specifically, it analyzes the conversation content using natural language processing technology and extracts stress factors.

[0491] Step 5:

[0492] The server stores the child's emotional state and stress factors in a database and performs long-term analysis. The input is the recognition results of the emotional state and stress factors, and the output is the database storage and analysis results. Specifically, the system uses a database management system (e.g., MySQL) to store the data and periodically analyzes it.

[0493] Step 6:

[0494] Parents receive notifications from the server and take appropriate action based on their child's mental health and stressors. The input is the notification from the server, and the output is the parent's response. Specifically, parents check the notification using a smartphone or computer and provide the necessary support.

[0495] Example 2

[0496] Next, a description will be given of Example 2 of Form 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."

[0497] Conventional devices for children lack systems that can properly analyze a child's emotional state and stress factors and provide notifications and advice to parents based on that analysis. This makes it difficult to understand a child's mental health in real time and take appropriate action.

[0498] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for analyzing the emotional state of the child, a means for adjusting the response of the AI ​​character based on the analysis result, a means for generating dialogue content using a generative AI model, and a means for sending a notification to the parent's terminal. This makes it possible to analyze the emotional state of the child in real time and take appropriate action. In addition, it is possible to quickly provide notifications and advice to the parent, thereby effectively supporting the child's mental health.

[0499] A "child-directed device" is an electronic device designed for use by children, including tablets and smartphones.

[0500] An "artificial intelligence character" is a virtual character programmed to analyze a child's emotions and stress levels through dialogue with them and respond appropriately.

[0501] "Emotional state" refers to a child's psychological state and includes emotions such as joy, sadness, and anger.

[0502] An "emotion analysis engine" is a software or hardware system that analyzes a child's facial expressions and tone of voice to identify their emotional state.

[0503] A "generative AI model" is an artificial intelligence model for generating natural language dialogue content based on an input prompt sentence.

[0504] "Dialogue content" refers to the words and phrases used by the AI ​​character in dialogue with the child.

[0505] "Parent device" means an electronic device designed for parental use, including smartphones and tablets.

[0506] "Notifications" are messages that inform parents about their child's emotional state and stressors.

[0507] "Advice" is a suggestion to provide parents with specific ways to deal with their child's emotional state or stressors.

[0508] This invention is a system installed in a device for children that provides an AI character that analyzes the emotional state of a child and responds appropriately based on that analysis. It also notifies parents of information about their child's emotional state and problems, and provides appropriate advice.

[0509] Hardware and software used

[0510] Hardware: Devices used by children (tablets and smartphones), smartphones used by parents

[0511] Software: Sentiment analysis engine, notification system, generative AI model

[0512] Data processing and calculation

[0513] 1. Emotion analysis:

[0514] The device uses a camera and microphone to capture the child's facial expressions and tone of voice in real time.

[0515] The device sends the captured data to an emotion analysis engine.

[0516] The emotion analysis engine uses machine learning models to analyze a child's emotional state, for example identifying emotions such as joy, sadness, or anger from facial expressions.

[0517] The emotion analysis engine sends the analysis results back to the device.

[0518] 2. AI character support:

[0519] The device determines the AI ​​character's response based on the emotional state received from the emotion analysis engine.

[0520] The device uses the generative AI model to generate dialogue based on the child's emotional state. For example, if a child is sad, the AI ​​character will respond empathetically, asking, "What's wrong? Did something happen?"

[0521] The device displays the generated dialogue on the AI ​​character and begins a dialogue with the child.

[0522] 3. Parental Notification and Advice:

[0523] The device sends information about the child's emotional state and problems to a server.

[0524] The server generates a notification to the parent based on the information it receives. For example, if a child is having trouble with friends at school, it generates a notification suggesting that the parent try to communicate with the child or seek professional help.

[0525] The server generates a notification and sends it to the parent's smartphone.

[0526] The parent's smartphone receives the notification and displays it to the parent.

[0527] Specific examples

[0528] Analysis of children's emotional state:

[0529] The device captures the child's face with a camera and records their voice with a microphone.

[0530] The device sends the captured data to an emotion analysis engine.

[0531] The emotion analysis engine determines that the child is sad and sends the result back to the device.

[0532] AI character support:

[0533] The device receives the analysis result that "the child is sad" and sends a prompt to the generative AI model.

[0534] The generative AI model generates the dialogue, "What's wrong? Is something wrong?"

[0535] The device displays the generated dialogue on an AI character, which responds empathetically to the child.

[0536] Parental Notice and Advice:

[0537] The device sends information to the server that "my child is having trouble with friendships at school."

[0538] The server generates a notification that says, "Your child appears to be having trouble with friendships at school. We recommend that you try to communicate with them or seek professional help."

[0539] The server generates a notification and sends it to the parent's smartphone.

[0540] The parent's smartphone receives the notification and displays it to the parent.

[0541] Prompt Sentence Examples

[0542] "If your child is struggling with friendships at school, generate a notification suggesting parents try to have a dialogue or seek professional help."

[0543] This system allows appropriate responses based on a child's emotional state, allowing parents to deal with their child's problems quickly.

[0544] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0545] Step 1:

[0546] The device uses a camera and microphone to capture the child's facial expressions and tone of voice in real time. The input is a video of the child's face and voice, and the output is these data. Specifically, the device's camera captures a picture of the child's face, and the microphone records the child's voice.

[0547] Step 2:

[0548] The device sends the captured data to the emotion analysis engine. The input is the facial video and voice data obtained in step 1, and the output is sending the data to the emotion analysis engine. Specifically, the device uploads the data to the emotion analysis engine via the network.

[0549] Step 3:

[0550] The emotion analysis engine uses a machine learning model to analyze the child's emotional state. The input is the facial video and voice data sent in step 2, and the output is the analysis result. Specifically, the emotion analysis engine analyzes facial expressions and voice tone to identify emotions such as joy, sadness, and anger.

[0551] Step 4:

[0552] The emotion analysis engine returns the analysis results to the terminal. The input is the analysis results obtained in step 3, and the output is data transmission to the terminal. Specifically, the emotion analysis engine sends the analysis results to the terminal via the network.

[0553] Step 5:

[0554] The device determines the AI ​​character's response based on the emotional state received from the emotion analysis engine. The input is the analysis result obtained in step 4, and the output is the AI ​​character's response. Specifically, the device analyzes the analysis result and selects an appropriate response.

[0555] Step 6:

[0556] The device uses the generative AI model to generate dialogue content that corresponds to the child's emotional state. The input is the response content and prompt determined in step 5, and the output is the generated dialogue content. Specifically, the device sends the prompt to the generative AI model to generate dialogue content. For example, the prompt could be "If the child is sad, generate an empathetic response."

[0557] Step 7:

[0558] The device displays the generated dialogue content on the AI ​​character and begins a dialogue with the child. The input is the dialogue content generated in step 6, and the output is the dialogue display of the AI ​​character. Specifically, the device displays the dialogue content on the AI ​​character and responds empathetically to the child, asking, "What's wrong? Is something wrong?"

[0559] Step 8:

[0560] The device sends information about the child's emotional state and problems to the server. The input is data about the child's emotional state and problems, and the output is sending data to the server. Specifically, the device uploads the data to the server via the network.

[0561] Step 9:

[0562] The server generates a notification for the parent based on the information it receives. The input is the data sent in step 8, and the output is the notification content. Specifically, the server generates the notification content based on the child's emotional state and problems. For example, it generates a notification that reads, "Your child appears to be having trouble with friendships at school. We recommend that you try to communicate with them or seek professional help."

[0563] Step 10:

[0564] The server sends the generated notification to the parent's smartphone. The input is the notification content generated in step 9, and the output is the notification sent to the parent's smartphone. Specifically, the server sends the notification to the parent's smartphone via the network.

[0565] Step 11:

[0566] The parent's smartphone receives the notification and displays it to the parent. The input is the notification content sent in step 10, and the output is the display of the notification. Specifically, the parent's smartphone receives the notification and displays a message to the parent saying, "It appears that your child is having trouble with friendships at school. We recommend that you try to communicate with them or seek professional help."

[0567] (Application example 2)

[0568] Next, a description will be given of Application Example 2 of Form 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."

[0569] Today's children face difficulties receiving appropriate support for dealing with stress and emotional fluctuations at school and at home. Parents, in particular, are required to quickly understand their children's emotional state and stress factors and respond appropriately. However, conventional methods have had difficulty analyzing children's emotional state in real time and providing specific advice to parents.

[0570] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0571] In this invention, the server is installed in a device for children and includes an AI character that performs regular stress checks, means for identifying the child's mental health condition and stress factors through conversation with the child, means for notifying the parents of the results and giving them advice, means for analyzing the child's emotional state in real time, means for taking appropriate action based on the analysis results, and means for providing specific advice to the parents. This enables parents to grasp the child's emotional state in real time and respond promptly and appropriately.

[0572] "Children's devices" are electronic devices intended for use by children, including smartphones, tablets, and smart glasses.

[0573] "Regular stress check" is the process of assessing a child's stress level at regular intervals.

[0574] An "AI character" is a virtual character equipped with artificial intelligence that has the ability to analyze a child's emotions and stress levels through dialogue with them.

[0575] "Methods for identifying a child's mental health condition and stress factors through conversations with the child" refers to a method for having a conversation with a child and identifying the child's mental health condition and stress factors from the content of the conversation.

[0576] "Means of informing parents of results and providing advice" refers to methods for informing parents of their child's emotional state and stress factors and suggesting appropriate ways of responding.

[0577] "Means for analyzing a child's emotional state in real time" refers to a method for instantly assessing a child's emotions and taking appropriate action based on the results.

[0578] "Means for taking appropriate action based on the analysis results" refers to a method for engaging in appropriate dialogue or taking appropriate action toward a child based on the results of emotion analysis.

[0579] "Means for providing specific advice to parents" are methods for suggesting specific ways of responding to parents based on their child's emotional state and stress factors.

[0580] The embodiments of the present invention will be described in detail below.

[0581] System Overview

[0582] The system is centered around an AI character installed on children's devices. The devices are electronic devices such as smartphones, tablets, and smart glasses. The AI ​​character identifies the child's emotional state and stress factors through dialogue with the child and notifies the parents of the results. It also takes appropriate action based on the analysis results and provides specific advice to the parents.

[0583] Hardware and software used

[0584] Hardware: Smartphones, tablets, smart glasses

[0585] Software: Python, virtual emotion engine library (EmotionEngine), virtual AI character library (AICharacter), SMTP library

[0586] Data processing and calculation

[0587] 1. Emotion Analysis: The device uses an emotion engine (Emotion Engine) to analyze the child's emotional state in real time. The emotion engine analyzes the child's facial expressions, tone of voice, and the content of the conversation to identify their emotional state.

[0588] 2. Response Generation: Based on the results of emotion analysis, the AI ​​Character generates an appropriate response. For example, if the child is sad, it will engage in empathetic dialogue, and if the child is happy, it will offer a pleasant topic.

[0589] 3. Notification and Advice: Parents are notified of the results of the emotion analysis and the appropriate response. The SMTP library is used to send a notification via email to the parent's smartphone. The notification includes specific advice based on the child's emotional state and stressors.

[0590] Specific examples

[0591] For example, if a child is having trouble making friends at school, the emotion engine will identify their emotional state as "sad." The AI ​​character will then engage in empathetic dialogue with the child and advise the parents, "Your child is having trouble making friends at school. Please try to talk to them or seek professional help."

[0592] Prompt Sentence Examples

[0593] "What advice would you offer parents if their child is struggling with friendships at school?"

[0594] In this way, the system can understand the child's emotional state in real time, allowing parents to respond quickly and appropriately.

[0595] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0596] Step 1:

[0597] The device launches an emotion engine (Emotion Engine) to analyze the child's emotional state in real time. As input, it receives data such as the child's facial expressions, tone of voice, and dialogue content. The emotion engine analyzes this data and identifies the child's emotional state (e.g., joy, sadness, anger, etc.). As output, it generates the identified emotional state.

[0598] Step 2:

[0599] The device launches an AI character (AICharacter) based on the emotional state obtained from the emotion engine. The identified emotional state is passed to the AICharacter as input. The AICharacter generates an appropriate response (e.g., empathetic dialogue or providing a fun topic) according to the emotional state. The generated response is output.

[0600] Step 3:

[0601] The device executes the generated response content against the child. As input, it receives the response content from the AI ​​character. The device executes the generated response content through dialogue with the child and observes the child's reaction. As output, it generates the child's reaction data.

[0602] Step 4:

[0603] The device notifies the parent based on the child's emotional state and stress factors. As input, it receives emotional state data from the emotion engine and response data from the AI ​​character. The device uses an SMTP library to send a notification via email to the parent's smartphone. The notification includes specific advice based on the child's emotional state and stress factors. As output, it generates the sent notification data.

[0604] Step 5:

[0605] The parent receives the notification from the device and checks the advice based on the child's emotional state and stress factors. The notification data from the device is acquired as input. The parent responds appropriately to the child based on the notification content. The parent's response action is generated as output.

[0606] In this way, the system can understand the child's emotional state in real time, allowing parents to respond quickly and appropriately.

[0607] Example 3

[0608] Next, a description will be given of a third embodiment of the third embodiment. 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."

[0609] Today's children often find it difficult to receive appropriate support for dealing with stress and emotional fluctuations at school and at home. A particularly serious problem is the inability of parents to grasp their children's emotional state in real time and respond appropriately. Therefore, there is a need for a system that can accurately analyze a child's emotional state and quickly notify parents.

[0610] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0611] In this invention, the server includes means for analyzing the content, tone, and facial expressions of the child's speech, means for identifying the child's emotional state by integrating the analysis results, and means for notifying the parent of the identified emotional state. This makes it possible to analyze the child's emotional state in real time and promptly notify the parent.

[0612] The "artificial intelligence character" is a program that analyzes a child's emotional state and stress factors through dialogue with them.

[0613] "Children's mental health status" refers to the emotional and stress levels a child is experiencing.

[0614] A "stressor" is an event or situation that causes stress to a child.

[0615] "Means for notifying parents of the results" refers to a method for informing parents of the analyzed emotional state and stress factors of their child.

[0616] "Advice tools" are methods that suggest appropriate responses to parents based on their child's emotional state and stressors.

[0617] "Methods for analyzing the content, tone, and facial expressions of speech" are methods for identifying a child's emotional state by analyzing the content of speech, tone of voice, and facial expressions.

[0618] The "means for integrating analysis results" refers to a method for identifying a child's emotional state by combining the results of voice analysis and facial expression analysis.

[0619] "Means for identifying emotional states" refers to methods for clarifying a child's emotional state based on the analyzed data.

[0620] A "parental notification method" is a method for informing a parent of an identified emotional state.

[0621] The present invention provides a system for analyzing a child's emotional state and notifying the parent of the results. The system includes a child-oriented terminal, a server, and a parent's terminal. Specific embodiments are described below.

[0622] Hardware and software used

[0623] Hardware: Camera, microphone, server, parent device (smartphone or PC)

[0624] Software: voice recognition software (e.g., voice recognition API), facial expression recognition software (e.g., facial expression recognition API), sentiment analysis engine (e.g., sentiment analysis API)

[0625] System configuration

[0626] 1. Device:

[0627] The device is equipped with a camera and microphone to collect the child's facial expressions and comments in real time.

[0628] For example, a child might say, "Something bad happened at school today," and the camera would capture their facial expression.

[0629] 2. Server:

[0630] The server converts the voice data sent from the terminal into text using a voice recognition API.

[0631] The converted text data is sent to the sentiment analysis API for sentiment analysis.

[0632] The server sends the video data obtained from the camera to an facial expression recognition API, which analyzes emotions from facial expressions.

[0633] For example, if the result of voice analysis is "sadness" and the result of facial expression analysis is "anger," these pieces of information are integrated.

[0634] The server integrates the results of voice analysis and facial expression analysis to identify the child's emotional state.

[0635] For example, if "sadness" and "anger" are detected at the same time, "events at school" will be identified as a stressor.

[0636] 3. Parent device:

[0637] The emotion engine notifies the parent of the identified emotional state.

[0638] Parents receive notifications via their smartphones or PCs to understand their children's emotional state.

[0639] For example, you might receive a notification that says, "Your child has had a bad experience at school. We are feeling sad and angry."

[0640] Specific examples

[0641] If a child says, "My friends ignored me today," audio and facial expressions are collected.

[0642] "Sadness" is detected through voice analysis, and "anger" is detected through facial expression analysis.

[0643] The emotion engine identifies "being ignored by friends" as the cause of stress and notifies the parents.

[0644] Prompt Sentence Examples

[0645] "Please explain the system that analyzes a child's voice and facial expressions when they say something bad happened at school and notifies the parent of their emotional state."

[0646] This system allows parents to understand their child's emotional state in real time and take appropriate action. The flow of the identification process in the third embodiment will be described with reference to FIG.

[0647] Step 1:

[0648] Data collection

[0649] The device uses a camera and microphone to collect the child's facial expressions and speech in real time.

[0650] Input: Child's speech and facial expression

[0651] Specific actions: For example, a child says, "Something bad happened at school today," and the camera captures their facial expression.

[0652] Output: Audio and video data are generated and sent to the server.

[0653] Step 2:

[0654] Converting audio data to text

[0655] The server converts the received voice data into text using a voice recognition API.

[0656] Input: Audio data

[0657] Specific operation: The server calls the speech recognition API and converts the voice data into text.

[0658] Output: The converted text data (e.g. "Something bad happened at school today")

[0659] Step 3:

[0660] Sentiment analysis of voice data

[0661] The server sends the converted text data to the sentiment analysis API for sentiment analysis.

[0662] Input: Text data

[0663] Specific operation: The server calls the sentiment analysis API and analyzes the text data.

[0664] Output: Sentiment analysis result (e.g. "sadness")

[0665] Step 4:

[0666] Emotion analysis of facial expression data

[0667] The server sends the received video data to an facial expression recognition API, which analyzes emotions from facial expressions.

[0668] Input: Video data

[0669] Specific operation: The server calls the facial expression recognition API and analyzes the video data.

[0670] Output: Facial expression analysis result (e.g. "Anger")

[0671] Step 5:

[0672] Integrating and identifying emotional states

[0673] The server integrates the results of voice analysis and facial expression analysis to identify the child's emotional state.

[0674] Input: Voice analysis results and facial expression analysis results

[0675] Specific operation: The server integrates the voice analysis result "sadness" and the facial expression analysis result "anger."

[0676] Output: Integrated emotional state (e.g., "What happened at school is stressful for me")

[0677] Step 6:

[0678] Parental Notification

[0679] The emotion engine notifies the parent of the identified emotional state.

[0680] Input: Integrated emotional state

[0681] Specific operation: The emotion engine generates a notification message and sends it to the parent's smartphone or PC.

[0682] Output: Parent notification message (e.g., "Your child has had a bad experience at school. We are feeling sad and angry.")

[0683] (Application example 3)

[0684] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[0685] In modern society, it is important to identify children's mental health conditions and stressors early and take appropriate measures. However, it is difficult for parents to understand their children's emotional state in real time, which can lead to overlooking problems they may be experiencing. In addition, there is a lack of systems that accurately analyze children's emotional states and notify parents, making it difficult for parents to take appropriate measures.

[0686] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server is installed in a terminal for children and includes an AI character that performs regular stress checks, means for identifying the child's mental health condition and stress factors through conversation with the child, means for notifying the results and giving advice to the parents, means for analyzing the child's facial expressions and tone of voice, and means for notifying the parents based on the analysis results. This enables parents to understand the child's emotional state in real time and take appropriate action.

[0687] A "child-directed device" is an electronic device designed for use by children.

[0688] "Regular stress checks" are the process of assessing a child's stress levels at regular intervals.

[0689] An "AI character" is a virtual character equipped with artificial intelligence that has the ability to interact with children.

[0690] "Conversation with a child" refers to the act of exchanging information between a child and an AI character through voice or text.

[0691] "Mental health" refers to a child's mental stability and sense of well-being.

[0692] A "stressor" is a cause or situation that causes stress to a child.

[0693] "Parent notification" refers to the act of communicating information about a child's emotional state and stressors to parents.

[0694] "Advice tools" are ways of suggesting appropriate actions or measures to children and parents.

[0695] "Means for analyzing a child's facial expressions and tone of voice" refers to technology that uses a camera and microphone to analyze a child's facial expressions and tone of voice.

[0696] "Means for notifying parents based on the analysis results" refers to a method for conveying information to parents based on the analyzed data.

[0697] The system for implementing this invention is installed in a device for children. The device includes an AI character that performs regular stress checks and has a means for identifying mental health conditions and stress factors through conversations with the child. It also includes a means for notifying parents of the results and providing advice.

[0698] Hardware and software used

[0699] Hardware: Smartphone camera and microphone

[0700] Software: OpenCV, Keras, SpeechRecognition, smtplib

[0701] System processing overview

[0702] 1. Initialize the camera:

[0703] The device's camera is initialized using OpenCV and the child's facial expressions are captured in real time.

[0704] 2. Emotion recognition:

[0705] The video frames acquired from the camera are converted to grayscale and face detection is performed. The detected face regions are input into an emotion recognition model (using Keras) to predict emotions.

[0706] 3. Speech Recognition:

[0707] The SpeechRecognition library is used to convert the audio captured from the microphone into text, which allows us to analyze what the child is saying.

[0708] 4. Notice:

[0709] If the emotion is "anger" or "sadness," the parent is notified by email. The email contains the emotional state and the content of the message. SMTPlib is used to send the email.

[0710] Specific examples

[0711] For example, if a child shows an angry expression in front of the camera and says, "I've had enough!", the system will recognize that emotion as "anger" and send the parent an email stating, "Child's emotional state: anger\nStatement: I've had enough!"

[0712] Prompt Sentence Examples

[0713] Develop an application that analyzes a child's emotional state in real time and notifies parents. Using the smartphone's camera and microphone, the application analyzes the child's facial expressions and tone of voice, and the emotion engine identifies stressors. Parents can understand their child's emotional state through the app and take appropriate action. The libraries used are OpenCV, Keras, SpeechRecognition, and smtplib.

[0714] In this way, a system can be realized that allows parents to grasp their child's emotional state in real time and take appropriate action.

[0715] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0716] Step 1:

[0717] The device initializes the camera using OpenCV, acquires video frames from the camera in real time, and captures the child's facial expressions. The input is the video frame from the camera, and the output is the captured video frame.

[0718] Step 2:

[0719] The device converts the captured video frame to grayscale, and then uses the OpenCV face detection algorithm to perform face detection. The input is the captured video frame, and the output is the detected face area.

[0720] Step 3:

[0721] The device preprocesses the detected face region to input it into the emotion recognition model. Specifically, the face region is resized to 48x48 pixels and normalized. The input is the detected face region, and the output is the preprocessed face image data.

[0722] Step 4:

[0723] The device inputs the preprocessed facial image data into an emotion recognition model built using Keras. The model predicts emotions from the facial image data. The input is the preprocessed facial image data, and the output is the predicted emotion.

[0724] Step 5:

[0725] The device analyzes the prediction results of the emotion recognition model and identifies the emotion with the highest probability. The input is the emotion prediction result, and the output is the identified emotion (e.g., anger, sadness).

[0726] Step 6:

[0727] The device uses the SpeechRecognition library to capture audio from the microphone and convert it to text. The input is the audio data from the microphone, and the output is the speech converted to text.

[0728] Step 7:

[0729] The device generates a message to notify the parent based on the identified emotion and the speech content converted into text. The input is the identified emotion and speech content, and the output is the notification message.

[0730] Step 8:

[0731] The terminal uses smtplib to generate and email notification messages to the parent. The input is the notification message and the output is the email sent.

[0732] In this way, the device will be able to analyze the child's emotional state in real time and notify the parents.

[0733] 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.

[0734] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ) 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.

[0735] Another example of generative AI is Gemini (registered trademark) (Internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[0736] 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.

[0737] [Second embodiment]

[0738] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0739] 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.

[0740] 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).

[0741] 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.

[0742] 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.

[0743] 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).

[0744] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for 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.

[0745] 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.

[0746] 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.

[0747] 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.

[0748] 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.

[0749] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0750] "Example 1"

[0751] In one embodiment of the present invention, an AI character installed on a device for children conducts stress checks through conversations with the child. The AI ​​character identifies mental health conditions and stress factors from the child's comments and reactions. For example, if a child avoids talking about school, the AI ​​character can identify school-related stress.

[0752] "Example 2"

[0753] The AI ​​character then notifies the parent of the results and offers advice. The notification is sent to the parent's smartphone using the device's notification function. The advice provides specific solutions to issues that are causing stress to the child. For example, if a child is having trouble with friends at school, the AI ​​character will suggest that the parent try to talk to the child or seek professional help.

[0754] "Example 3"

[0755] The AI ​​character also analyzes the child's emotional state based on the content, tone, and facial expressions of the child's speech. For example, if the child expresses anger or sadness, the AI ​​character analyzes this information and identifies the cause of stress.

[0756] The processing flow of each embodiment will be described below.

[0757] "Example 1"

[0758] Step 1: The AI ​​character initiates a conversation with the child. This conversation can be initiated by the child interacting with the device, or by the AI ​​character periodically prompting the conversation.

[0759] Step 2: The AI ​​character will engage in conversation to explore the child's mental health and stressors, collecting information through questions such as, "How was your day?" and "Did anything interesting happen at school?"

[0760] Step 3: The AI ​​character analyzes the collected information and assesses the child's stress level, using AI natural language processing and machine learning techniques.

[0761] "Example 2"

[0762] Step 1: The AI ​​character notifies the parent of the analysis results. This notification is sent via the device's notification function directly to the parent's smartphone.

[0763] Step 2: The notification will include the child's stress level, its contributing factors, and recommendations. The recommendations will provide specific action plans to reduce the child's stress.

[0764] "Example 3"

[0765] Step 1: The AI ​​character analyzes the child's emotional state based on the content, tone, and facial expressions of the child's speech.

[0766] Step 2: The AI ​​character uses the emotional state analysis results to identify the child's stressors. For example, if the child expresses anger or sadness, the AI ​​character analyzes that information and identifies the stressors.

[0767] Step 3: Based on the identified stressors, the AI ​​character generates advice for the child and parent, providing specific courses of action to reduce the stressors.

[0768] Example 1

[0769] Next, a description will be given of Example 1 of Form 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."

[0770] Today's children are often exposed to stress at school and at home, making it important to properly understand their mental health. However, it is difficult for parents and teachers to accurately understand a child's stress and emotional state, which can delay appropriate responses. Furthermore, children often have difficulty expressing their own stress and emotions effectively. This has led to a need for effective methods to properly manage children's mental health.

[0771] The identification process by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. In this invention, the server is installed in a terminal for children and includes an AI character that performs regular stress checks, a means for identifying the child's mental health state and stress factors through conversation with the child, a means for notifying the results and providing advice to the parent, a means for collecting the child's comments and sending them to the generative AI model, and a means for receiving the analysis results from the generative AI model and providing appropriate feedback and advice to the child. This makes it possible to grasp the child's mental health state in real time and take appropriate measures quickly.

[0772] A "child-directed device" is an electronic device designed for use by children.

[0773] "Regular stress checks" are the process of assessing a child's stress level at regular intervals.

[0774] An "artificial intelligence character" is a virtual character that interacts with children using artificial intelligence technology.

[0775] "Conversation with a child" refers to the act of a child communicating with an AI character through voice or text.

[0776] "Mental health" refers to a child's mental stability and emotional state.

[0777] "Stressors" refer to causes or situations that cause stress to children.

[0778] "Notifying parents of results" refers to the act of communicating information about a child's mental health and stress factors to parents.

[0779] "Advice tools" are methods for providing appropriate advice and instruction to children and parents.

[0780] "Means of collecting statements" refers to the method of recording children's statements and saving them as data.

[0781] A "generative artificial intelligence model" is a model generated using artificial intelligence technology that performs natural language processing and sentiment analysis.

[0782] "Means for receiving analysis results" refers to a method for importing analysis results from a generative artificial intelligence model into a terminal.

[0783] "Means for providing appropriate feedback and advice" refers to methods for providing appropriate responses and advice to children based on the analysis results.

[0784] MODE FOR CARRYING OUT THE INVENTION

[0785] This invention is a system that uses an AI character installed on a device for children to identify a child's mental health condition and stress factors, and notifies the parents of the results and provides advice. A specific embodiment of this system is described below.

[0786] Program Generation

[0787] The server generates the AI ​​character program to be installed on the device for children. This program uses natural language processing technology to analyze conversations with children and identify their mental health status and stress factors. Specifically, the program is developed using programming languages ​​such as Python and Java and distributed to the device via AWS (Amazon Web Services) or Google Cloud Platform.

[0788] Program processing

[0789] The terminal installs the distributed program and starts the AI ​​character. The user (child) operates the terminal and starts a conversation with the AI ​​character. For example, if the user says "Hello," the AI ​​character will reply, "Hello, how was your day?"

[0790] The device uses a microphone to collect the user's speech. The collected voice data is converted into text in real time and sent to the generative AI model. For example, if a user says, "Nothing fun happened at school today," the text data is sent to the generative AI model.

[0791] The generative AI model analyzes the text data sent. Specifically, it uses generative AI models such as Google's Dialogflow and OpenAI's GPT-3 to identify emotions and stress factors from the user's speech. The analysis results indicate that the user is likely to have negative feelings toward school.

[0792] The device receives the analysis results from the generative AI model. For example, if the device determines that the user has negative feelings about school, it uses voice synthesis technology to provide feedback to the user, such as, "Have you had any problems at school?"

[0793] Examples and prompts

[0794] As a concrete example, the following conversation can be considered:

[0795] User (child): "Nothing fun happened at school today."

[0796] AI character: "Oh yeah. Did you get in trouble at school?"

[0797] From this conversation, the AI ​​character identifies the possibility that the child has negative feelings about school.

[0798] Examples of prompts to be input to a generative AI model include:

[0799] Prompt: "What stressors might be causing your child to avoid talking about school?"

[0800] By inputting this prompt into the generative AI model, the AI ​​character can generate appropriate feedback and advice.

[0801] As described above, this invention is a system that makes it possible to grasp a child's mental health condition in real time and to take appropriate measures quickly.

[0802] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0803] Step 1:

[0804] The server generates programs for AI characters to be installed on children's devices and distributes them to the devices. Specifically, the server develops programs using programming languages ​​such as Python and Java and distributes them to devices via AWS or Google Cloud Platform. The input is the program source code, and the output is a program that can be installed on the device.

[0805] Step 2:

[0806] The terminal installs the distributed program and starts the AI ​​character. The user (child) operates the terminal and starts a conversation with the AI ​​character. Specifically, when the user says "Hello," the AI ​​character replies "Hello, how was your day?" The input is the user's voice, and the output is the AI ​​character's response.

[0807] Step 3:

[0808] The device uses a microphone to collect user speech and converts it into text in real time. The collected speech data is then converted into text using speech recognition technology. The input is the user's speech data, and the output is text data.

[0809] Step 4:

[0810] The device sends the generated text data to the generative AI model. Specifically, the device sends the text data to the generative AI model on the server via the Internet. The input is the text data, and the output is the data sent to the generative AI model.

[0811] Step 5:

[0812] The generative AI model analyzes the submitted text data and identifies mental health conditions and stress factors. Specifically, the generative AI model uses natural language processing technology to analyze the text data and identify emotions and stress factors. The input is the text data, and the output is the analysis results.

[0813] Step 6:

[0814] The device receives the analysis results from the generative AI model and provides appropriate feedback and advice to the user. Specifically, the device uses voice synthesis technology to provide feedback to the user based on the analysis results. For example, if it is determined that the user has negative feelings toward school, the device will provide feedback such as, "Have you had any trouble at school?" The input is the analysis results, and the output is feedback generated for the user.

[0815] Step 7:

[0816] The device notifies the parent of the analysis results and feedback. Specifically, the device sends notifications via the Internet to the parent's smartphone or email address. The inputs are the analysis results and feedback, and the output is a notification to the parent.

[0817] (Application example 1)

[0818] Next, a description will be given of Application Example 1 of Form 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."

[0819] Today's children often experience stress due to various factors, including school and home environments. However, it is difficult for children themselves to recognize this stress and deal with it appropriately. It is also not easy for parents and educators to understand a child's stress level and respond early. Therefore, there is a need for a system that regularly checks children's mental health, identifies stress factors, and provides appropriate advice.

[0820] 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.

[0821] In this invention, the server is installed in a device for children and includes an AI character that performs regular stress checks, means for identifying the child's mental health condition and stress factors through conversation with the child, means for notifying the parents of the results and providing advice, means for using a generative AI model to evaluate the stress level from the child's comments and reactions, means for notifying the parents or experts when the stress level is high, and means for providing regular reports on the child's mental health condition, which makes it possible to detect a child's stress state early and take appropriate measures.

[0822] A "child-directed device" is an electronic device designed for use by children.

[0823] "Regular stress checks" are the process of assessing a child's stress level at regular intervals.

[0824] An "AI character" is a virtual character equipped with artificial intelligence that has the ability to collect and analyze information through dialogue with children.

[0825] "Conversation with a child" refers to the act of exchanging information between a child and an AI character through voice or text.

[0826] "Mental health" refers to a child's mental and emotional stability.

[0827] "Stressors" refer to causes or situations that cause stress to children.

[0828] "Means of notifying parents of results and providing advice" refers to methods for conveying information about their child's stress level and mental health status to parents and encouraging them to take appropriate measures.

[0829] The "generative AI model that assesses stress levels from children's statements and reactions" is an artificial intelligence model that analyzes children's behavior and words and determines the level of stress.

[0830] "Means to notify parents and professionals when stress levels are high" refers to a method to communicate this information to parents and professionals when a child's stress level exceeds a certain threshold.

[0831] "Means for providing regular reports on children's mental health status" refers to a method for regularly compiling information on children's mental health status and reporting it to parents and professionals.

[0832] The system for carrying out this invention is mainly composed of an AI character installed on a device for children. A specific embodiment of this system will be described below.

[0833] System configuration

[0834] The system consists of the following main components:

[0835] 1. Child-directed devices: Electronic devices such as smartphones and tablets used by children.

[0836] 2. AI Character: A virtual character equipped with artificial intelligence that collects and analyzes information through dialogue with children.

[0837] 3. Generative AI model: An artificial intelligence model for assessing stress levels from children's statements and reactions.

[0838] 4. Notification system: A system to notify parents and professionals when stress levels are high.

[0839] 5. Reporting system: A system that provides regular reports on children's mental health status.

[0840] Program processing

[0841] The server does the following:

[0842] 1. Conversation collection: Collect conversations between a child and an AI character in text format. For example, a child might answer "Hmm, nothing in particular" to the question "What did you do at school today?"

[0843] 2. Stress Level Analysis: Using a generative AI model, we assess stress levels from collected conversations. We use OpenAI's API to analyze conversations and determine the level of stress.

[0844] 3. Notification: Notify parents or professionals when stress levels are high, for example, by sending a message saying "Warning: Child's stress level is high."

[0845] 4. Generate reports: Regularly summarize the child's mental health status and provide it as a report to parents and professionals.

[0846] Hardware and software used

[0847] Hardware: smartphones, tablets, servers

[0848] Software: OpenAI API, generative AI models

[0849] Specific examples

[0850] Below are some examples of specific conversations and prompts:

[0851] Example conversation

[0852] AI: What did you do at school today?

[0853] Child: Hmm, nothing in particular.

[0854] AI: Did you hang out with friends?

[0855] Child: No, not really.

[0856] Prompt Sentence Examples

[0857] Assess your child's stress level from the following conversation:

[0858] AI: What did you do at school today?

[0859] Child: Hmm, nothing in particular.

[0860] AI: Did you hang out with friends?

[0861] Child: No, not really.

[0862] evaluation:

[0863] In this way, the system can detect stress in children early and take appropriate measures.

[0864] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0865] Step 1:

[0866] Conversation collection

[0867] The device collects conversations between the child and the AI ​​character in text format. Specifically, when the child speaks to the device, the speech is converted into text and saved as a conversation log. The input is the child's speech, and the output is a text-format conversation log.

[0868] Step 2:

[0869] Stress level analysis

[0870] The server inputs the collected conversation logs into a generative AI model to evaluate stress levels. Specifically, it uses OpenAI's API to analyze the conversation content and determine the degree of stress. The input is a text-format conversation log, and the output is an evaluation result of the stress level.

[0871] Step 3:

[0872] notification

[0873] If the stress level is high, the server notifies the parent or expert. Specifically, based on the stress level assessment result, it sends a message to the parent or expert saying, "Warning: Your child's stress level is high." The input is the stress level assessment result, and the output is the notification message.

[0874] Step 4:

[0875] Generate reports

[0876] The server periodically summarizes the child's mental health status and provides it to parents and specialists as a report. Specifically, it aggregates conversation logs and stress level assessment results over a certain period of time and generates a report. The input is the conversation logs and stress level assessment results over a certain period of time, and the output is a mental health status report.

[0877] Step 5:

[0878] Providing advice

[0879] The server identifies the causes of stress and provides corresponding advice. Specifically, it uses a generative AI model to analyze the causes of stress and generate appropriate advice. The input is the conversation log and the stress level assessment results, and the output is the content of the advice.

[0880] Example 2

[0881] Next, a description will be given of Example 2 of Form 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."

[0882] Today's children are often exposed to stress at school and at home, and it is necessary to detect this stress early and deal with it appropriately. However, it is difficult for parents to accurately grasp their children's stress levels and provide appropriate advice. With conventional methods, there is a lack of a system in place to identify the causes of children's stress and notify parents, making it difficult to protect children's mental health.

[0883] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for transmitting generated data to a cloud server, a means for the cloud server to analyze the stress level using the generated AI model, and a means for the cloud server to generate notification content and advice based on the analysis result. This makes it possible to detect stress in children early and provide appropriate advice to parents.

[0884] The "artificial intelligence character" is a program that is installed on devices for children, conducts regular stress checks, and identifies mental health conditions and stress factors through conversations with children.

[0885] The "cloud server" is a remote server that receives data via the internet, analyzes stress levels using a generative AI model, and generates notifications and advice based on the analysis results.

[0886] A "generative AI model" is an artificial intelligence algorithm that analyzes the received data and assesses a child's stress level.

[0887] The "notification function" is a function that enables the terminal to send notification of results and advice to the parent's information terminal.

[0888] A "stress check" is a process of collecting data on a child's behavior and emotions to assess the presence and level of stress.

[0889] "Analysis results" are information about stress levels and factors that the generative AI model outputs based on input data.

[0890] "Advice" refers to specific solutions or suggestions provided to parents based on the analysis results.

[0891] "Data transmission means" refers to the functions and protocols for transmitting data from the terminal to the cloud server.

[0892] This invention is a system that uses an AI character installed on a device for children to periodically check a child's stress level, notify the parents of the results, and provide appropriate advice. This system is implemented using the following hardware and software.

[0893] Hardware and software used

[0894] Hardware: Smartphones, cloud servers

[0895] Software: Generative AI model, notification function (depending on smartphone OS)

[0896] Specific operation of the system

[0897] 1. The user enters data to measure the child's stress level.

[0898] Users open a smartphone app and answer questions about their child's behavior and emotions.

[0899] Example: A user fills out an app's questionnaire form and responds to the prompt, "Tell us about any recent changes in your child's behavior or emotions" by typing, "He recently had a fight with a friend at school."

[0900] 2. The device sends the entered data to the cloud server.

[0901] When the smartphone app presses the "send" button, the data is uploaded to a cloud server via the Internet.

[0902] 3. The server inputs the received data into a generative AI model to analyze stress levels.

[0903] The server passes the data to a generative AI model implemented in Python, which determines the stress level as "high" based on the information that the user "had a fight with a friend."

[0904] 4. Based on the analysis results, the server identifies the child's stress factors and generates notifications and advice for parents.

[0905] The server generates a message saying, "Your child is having trouble with friendships at school. We suggest you try to communicate with them or seek professional help."

[0906] 5. The server generates notifications and sends advice to the device.

[0907] The server generates a message and sends it to a smartphone app, which receives the message.

[0908] 6. The device uses the notification function to send a notification to the parent's smartphone.

[0909] A notification will appear in the notification bar on your smartphone saying, "We have an important message for you regarding stress in children."

[0910] Prompt Sentence Examples

[0911] "Tell me what problems your child has been having at school recently."

[0912] "Tell me about any recent changes in your child's behavior or emotions."

[0913] This system will enable parents to detect stress in their children early and provide appropriate coping strategies, thereby strengthening support for protecting children's mental health.

[0914] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0915] Step 1:

[0916] The user inputs data to measure the child's stress level.

[0917] Input: A user opens a smartphone app and answers questions about their child's behavior and emotions.

[0918] What happens: A user fills out an app questionnaire prompting them to "Tell us about any recent changes in your child's behavior or emotions," and answers, "They recently had a fight with a friend at school."

[0919] Output: The input data is saved in the smartphone app.

[0920] Step 2:

[0921] The terminal transmits the input data to the cloud server.

[0922] Input: User input data stored in the smartphone app.

[0923] Specific operation: When the smartphone app presses the "send" button, the data is uploaded to a cloud server via the Internet.

[0924] Output: Data is sent to the cloud server.

[0925] Step 3:

[0926] The server inputs the received data into a generative AI model to analyze stress levels.

[0927] Input: User input data sent to the cloud server.

[0928] Specific operation: The server passes data to a generative AI model implemented in Python, which determines the stress level as "high" based on the information that "you had a fight with a friend."

[0929] Output: Stress level analysis results are generated.

[0930] Step 4:

[0931] Based on the analysis results, the server identifies the child's stress factors and generates notifications and advice to be sent to parents.

[0932] Input: Stress level analysis results from a generative AI model.

[0933] Specific behavior: The server generates a message saying, "Your child is having trouble with friendships at school. We suggest you try to communicate with them or seek professional help."

[0934] Output: Notifications and advice are generated.

[0935] Step 5:

[0936] The server generates notifications and advice and sends them to the terminal.

[0937] Input: Generated notification content and advice.

[0938] Specific operation: The server generates a message and sends it to the smartphone app, which then receives the message.

[0939] Output: Notifications and advice are sent to the smartphone app.

[0940] Step 6:

[0941] The device uses the notification function to send a notification to the parent's smartphone.

[0942] Input: Notifications and advice sent by the server.

[0943] What it does: A notification will appear in your smartphone's notification bar saying, "We have an important message for you about your child's stress."

[0944] Output: A notification will appear on the parent's smartphone.

[0945] (Application example 2)

[0946] Next, a description will be given of Application Example 2 of Form 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."

[0947] Today's children often experience stress due to various factors, including school, home, and friendships. However, children themselves are often unable to express their stress appropriately, making it difficult for parents to understand the situation. It is also difficult for parents to understand their children's stressors and find appropriate ways to deal with them. This puts children at risk of developing poor mental health. This invention aims to protect children's mental health by identifying their stressors and providing appropriate advice to parents.

[0948] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server is installed in a terminal for children and includes an AI character that performs regular stress checks, means for identifying the child's mental health condition and stress factors through conversation with the child, means for notifying the results and providing advice to the parent, means for identifying the child's stress factors using a generative AI model, means for generating specific advice for the identified stress factors, and means for sending a notification to the parent's terminal. This makes it possible to quickly and accurately identify the child's stress factors and provide appropriate advice to the parent.

[0949] A "child-directed device" is an electronic device designed for use by children.

[0950] "Regular stress checks" are the process of assessing a child's stress levels at regular intervals.

[0951] An "artificial intelligence character" is a virtual character that uses AI technology to interact with children and analyze their emotions and stress.

[0952] "Children's mental health" refers to a child's mental health and emotional stability.

[0953] "Stressors" refer to the causes and situations that cause children to feel stressed.

[0954] "Means of notifying parents of results and giving advice" refers to methods and functions for informing parents of their child's stress level and how to deal with it.

[0955] A "generative AI model" is a model that has been trained using artificial intelligence to perform a specific task.

[0956] "Specific advice for identified stressors" refers to specific coping strategies or suggestions provided based on the detected causes of stress.

[0957] "Means for sending notifications to parent's terminal" refers to a method or function for sending information to the electronic device used by the parent.

[0958] The system for implementing this invention is composed of a terminal for children, a server, and a terminal for parents. Each component and its function will be explained below.

[0959] Children's devices

[0960] The device for children is equipped with an AI character that periodically converses with the child to identify their mental health and stressors. The content of the conversation is converted into text data using voice recognition technology and sent to a server.

[0961] server

[0962] The server uses a generative AI model to identify the child's stressors, using prompts such as the following to input the AI ​​model:

[0963] 1. Identifying stressors:

[0964] Identify stressors if your child is struggling with: Having trouble with friendships at school.

[0965] 2. Providing advice:

[0966] What advice should you offer parents if their child is struggling with friendships at school?

[0967] The server inputs these prompts into a generative AI model and uses the results to identify the child's stressors. It then generates specific advice for each identified stressor.

[0968] Parent's device

[0969] The parent's device will receive a notification sent from the server, which will include information about the child's stressors and specific advice on how to address them, allowing the parent to take appropriate measures to support their child's mental health.

[0970] Hardware and software used

[0971] Children's devices: smartphones, tablets, smart speakers, etc.

[0972] Server: Cloud server (e.g. AWS, Google Cloud)

[0973] Parent's device: smartphone, tablet, PC, etc.

[0974] Software: Python, OpenAI API, SMTP server (e.g. Gmail SMTP)

[0975] Specific examples

[0976] For example, if a child says to the device, "I'm having trouble with friends at school," the process will proceed as follows:

[0977] 1. The child's device converts the voice into text data and sends it to the server.

[0978] 2. The server uses a generative AI model to identify the stressor and uses the following prompt:

[0979] Identify stressors if your child is struggling with: Having trouble with friendships at school.

[0980] 3. The server generates advice for the identified stressors and uses the following prompt:

[0981] What advice should you offer parents if their child is struggling with friendships at school?

[0982] 4. The server notifies the parent device of the results obtained.

[0983] In this way, it becomes possible to quickly and accurately identify stressors in children and provide appropriate advice to parents.

[0984] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0985] Step 1:

[0986] A device for children begins a dialogue with the child. The device uses voice recognition technology to convert what the child says into text data. The input is the child's voice, and the output is text data. This text data serves as the basis for identifying the child's mental health status and stress factors.

[0987] Step 2:

[0988] The terminal sends the converted text data to the server. The input is text data, and the output is data sent to the server. The server receives this data and proceeds to the next processing step.

[0989] Step 3:

[0990] The server uses a generative AI model to identify children's stressors from text data. The input is the text data, and the output is the stressor identification results. The server inputs the AI ​​model using the following prompt sentence:

[0991] Identify stressors if your child is experiencing: [Text data]

[0992] The generative AI model identifies stressors based on this prompt.

[0993] Step 4:

[0994] The server generates specific advice for the identified stressors. The input is the stressor identification result, and the output is the specific advice. The server inputs the following prompt to the AI ​​model:

[0995] What advice should you offer parents if their child is struggling with [stressor]?

[0996] The generative AI model generates specific advice based on this prompt.

[0997] Step 5:

[0998] The server notifies the parent device of the generated advice and the results of identifying stress factors. The input is the advice and the results of identifying stress factors, and the output is the notification to the parent device. The server uses an SMTP server to send the notification to the parent's email address.

[0999] Step 6:

[1000] The parent's device receives the notification and the parent checks the content. The input is the notification from the server, and the output is the information the parent checks. Based on this information, the parent can take appropriate measures to support their child's mental health.

[1001] In this way, it becomes possible to quickly and accurately identify stressors in children and provide appropriate advice to parents.

[1002] Example 3

[1003] Next, a description will be given of Example 3 of Form Example 3. 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."

[1004] Previous stress check systems for children had the problem of being unable to accurately identify a child's emotional state and stress factors. Furthermore, they lacked the means to provide appropriate advice to parents, making it difficult to effectively manage their children's mental health.

[1005] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1006] In this invention, the server includes means for capturing the child's voice and video, means for converting the captured voice data into text, means for analyzing facial expressions from the video data, means for analyzing the text data and identifying the emotional state, and means for reporting the emotional state and its cause to the parent. This makes it possible to accurately identify the child's emotional state and stress factors and provide appropriate advice to the parent.

[1007] A "child-directed device" is an electronic device designed for use by children.

[1008] "Regular stress checks" are the process of assessing a child's stress levels at regular intervals.

[1009] An "artificial intelligence character" is a virtual character programmed to interact with children and analyze their emotions and stress levels.

[1010] "Children's mental health" refers to the state of a child's mental and emotional health.

[1011] "Stressors" refer to causes or situations that cause stress to children.

[1012] "Means of notifying parents of results and giving advice" refers to methods and functions for communicating analysis results to parents and proposing appropriate countermeasures.

[1013] "Means for capturing audio and video of children" refers to the ability to collect audio and video of children using a microphone and camera.

[1014] The "means for converting captured voice data into text" is a function that converts voice data into text data using voice recognition technology.

[1015] "Means for analyzing facial expressions from video data" refers to a function that uses video analysis technology to recognize a child's facial expressions and identify their emotional state.

[1016] The "means for analyzing text data and identifying an emotional state" is a function that uses natural language processing technology to analyze text data and determine a child's emotional state.

[1017] "Means for reporting emotional state and its causes to parents" refers to methods or functions for conveying the analysis results to parents and explaining the child's emotional state and its causes.

[1018] This invention is a system that uses an AI character installed on a device for children to identify a child's mental health condition and stress factors and notify the parents of the results. A specific embodiment of this system is described below.

[1019] First, the user (parent) prepares a device for the child to use. This device is equipped with a microphone and camera, and can capture the child's voice and video. The device captures the child's speech and facial expressions in real time and sends this data to the server.

[1020] The server converts the received audio data into text using Google Cloud Speech-to-Text. This process captures the child's speech as text data. The server then analyzes the child's facial expressions from the video data using the Microsoft Azure Face API. This identifies the child's emotional state.

[1021] Additionally, the server uses OpenAI's GPT-3 to analyze the text data and IBM Watson Tone Analyzer to identify the emotional state, making it clear what emotions the child is feeling. For example, if a child says, "I had a fight with my friend at school today," and shows an angry expression, the server will identify that the child is feeling angry.

[1022] Finally, the server reports the analysis results to the user (parent). For example, it may notify the parent that "your child is feeling angry because of a fight at school." This notification may also include appropriate advice. For example, it may provide specific advice such as "It is important to talk with your child and understand the cause of the fight."

[1023] As a concrete example, the following prompt sentence can be used:

[1024] Prompt: "Analyze audio and video recordings of a child talking about an incident at school and identify their emotional state. In particular, if they express anger or sadness, identify the cause of this."

[1025] In this way, the present invention can accurately identify the emotional state and stress factors of a child and provide appropriate advice to the parents. The flow of the identification process in the third embodiment will be described with reference to FIG.

[1026] Step 1:

[1027] The device captures audio and video of the child.

[1028] Specifically, the device uses a microphone and camera to record the child's voice and facial expressions in real time.

[1029] Input: Child's audio and video

[1030] Output: Captured audio and video data

[1031] Step 2:

[1032] The device sends the captured data to the server.

[1033] Specifically, the device transmits the captured audio and video data to the server using a secure communication protocol (e.g., HTTPS).

[1034] Input: Captured audio and video data

[1035] Output: Audio and video data sent to the server

[1036] Step 3:

[1037] The server converts the audio data into text.

[1038] Specifically, the server uses Google Cloud Speech-to-Text to convert the received voice data into text data.

[1039] Input: Audio data

[1040] Output: Text data

[1041] Step 4:

[1042] The server analyzes facial expressions from the video data.

[1043] Specifically, the server uses the Microsoft Azure Face API to analyze the child's facial expressions from the received video data and identify their emotional state.

[1044] Input: Video data

[1045] Output: Analyzed facial expression data

[1046] Step 5:

[1047] The server analyzes the text data to identify the emotional state.

[1048] Specifically, the server uses OpenAI's GPT-3 to analyze text data and IBM Watson Tone Analyzer to identify emotional states.

[1049] Input: Text data

[1050] Output: Identified emotional state

[1051] Step 6:

[1052] The server reports the emotional state and its cause to the user.

[1053] Specifically, the server notifies the user (parent) of the analysis results, explains the child's emotional state and its causes, and provides appropriate advice.

[1054] Input: Identified emotional state and its cause

[1055] Output: Analysis results and advice reported to the user

[1056] (Application example 3)

[1057] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[1058] Today's children are often exposed to stress and emotional fluctuations at home and school, which can result in poor mental health. However, it is difficult for parents and guardians to understand their children's emotional state and stressors in real time. Furthermore, if children are unable to express their emotions appropriately, problems may go unnoticed. This can delay appropriate measures to protect children's mental health.

[1059] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1060] In this invention, the server is installed in a device for children and includes an artificial intelligence character that performs regular stress checks, means for identifying the child's mental health condition and stress factors through conversation with the child, means for notifying the parents of the results and providing advice, means for analyzing the child's voice data and analyzing the emotional state, means for analyzing the child's video data and analyzing the emotional state from facial expressions, means for integrating the results of the emotion analysis of the voice data and video data and detecting abnormalities, and means for notifying the parents or guardians when an abnormality is detected. This makes it possible to grasp the child's emotional state and stress factors in real time, detect abnormalities early, and take appropriate action.

[1061] A "child-directed device" is an electronic device designed for use by children.

[1062] "Regular stress checks" are the process of assessing a child's stress levels at regular intervals.

[1063] An "artificial intelligence character" is a virtual character that uses AI technology to interact with children and analyze their emotions and stress.

[1064] "Conversation with a child" refers to the act of a child communicating with an AI character through voice or text.

[1065] "Mental health" refers to a child's mental and emotional stability and well-being.

[1066] "Stressors" refer to causes or situations that cause stress to children.

[1067] "Parent notification" refers to the act of informing parents or guardians of the results of the assessment of their child's emotional state and stress level.

[1068] "Advice tools" are ways of suggesting appropriate responses or actions to children and parents.

[1069] "Analyzing audio data" is the process of analyzing the content and tone of a child's speech to identify their emotional state.

[1070] "Means for analyzing emotional states" are techniques and methods for assessing a child's emotions from their voice and facial expressions.

[1071] "Analyzing video data" is the process of analyzing a child's facial expressions and movements to identify their emotional state.

[1072] "Means for analyzing emotional states from facial expressions" refers to techniques and methods that use video data to analyze children's facial expressions and evaluate their emotions.

[1073] "Sentiment analysis integration" refers to the process of combining the analysis results of audio data and video data to assess the overall emotional state.

[1074] "Anomaly detection methods" are techniques or methods for identifying unusual emotional states or stress levels.

[1075] "Means for notifying parents or guardians" refers to the method by which information about an abnormality is notified to parents or guardians when it is detected.

[1076] The system for implementing this invention is installed in a device for children. The device includes an AI character that performs regular stress checks and identifies mental health conditions and stress factors through conversations with the child. It also has a function to notify parents of the results and provide advice.

[1077] Hardware and software used

[1078] Hardware: smartphone, tablet, camera, microphone

[1079] Software: Python, OpenCV, TensorFlow, Transformers (Hugging Face emotion analysis model), DeepFace

[1080] Data processing and calculation

[1081] 1. Voice data analysis: The device's microphone is used to collect the child's voice, and a speech recognition model (Transformers) is used to analyze the child's emotional state. The voice data is converted into text and sentiment analysis is performed.

[1082] 2. Video Data Analysis: We collect video data of children using the device camera and analyze their emotional state from facial expressions using OpenCV and DeepFace. The video data is analyzed frame by frame, and emotions are identified from facial expressions.

[1083] 3. Sentiment Analysis Integration: The sentiment analysis results of audio and video data are integrated to evaluate the overall emotional state. If an anomaly is detected, a notification will be sent to parents or guardians.

[1084] Specific examples

[1085] For example, if a child says "I'm scared," and the speech recognition model detects "fear" and the facial expression recognition model also detects "fear," the system will detect an anomaly and send a notification to the parent, including the cause of the child's fear and advice on what the parent should do.

[1086] Prompt Sentence Examples

[1087] Please enter your child's voice data.

[1088] "Please enter your child's video data."

[1089] In this way, it is possible to grasp a child's emotional state and stress factors in real time, detect abnormalities early, and take appropriate action.

[1090] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1091] Step 1:

[1092] The device collects the child's voice data through a microphone. The input is the child's voice, and the output is a voice data file. This voice data is saved for subsequent voice recognition processing.

[1093] Step 2:

[1094] The device inputs the collected voice data into a voice recognition model (Transformers) and converts it into text data. The input is a voice data file, and the output is text data. This text data is used for sentiment analysis.

[1095] Step 3:

[1096] The device inputs the converted text data into a sentiment analysis model to identify the emotional state. The input is the text data, and the output is the emotional state (e.g., joy, sadness, fear, etc.). This emotional state is used in subsequent processing.

[1097] Step 4:

[1098] The device collects video data of the child through a camera. The input is the child's video, and the output is a video data file. This video data is saved for subsequent facial expression recognition processing.

[1099] Step 5:

[1100] The device inputs the collected video data into a facial expression recognition model (OpenCV and DeepFace) to identify the emotional state from the facial expressions. The input is a video data file, and the output is the emotional state (e.g., joy, sadness, fear, etc.). This emotional state is used in subsequent processing.

[1101] Step 6:

[1102] The terminal integrates the emotion analysis results of the audio data and the video data to evaluate the overall emotional state. The input is the emotional state of the audio data and the emotional state of the video data, and the output is the integrated emotional state. This integrated emotional state is used for anomaly detection.

[1103] Step 7:

[1104] The device detects anomalies based on the integrated emotional state. The input is the integrated emotional state, and the output is the anomaly detection result. If an anomaly is detected, a notification is sent to the parent or guardian.

[1105] Step 8:

[1106] The device sends a notification to parents or guardians when an abnormality is detected. The input is the anomaly detection result, and the output is a notification message. This notification message includes the child's emotional state, stress factors, and advice on what the parent should do.

[1107] 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.

[1108] "Example 1"

[1109] One embodiment of the present invention is a system that includes an emotion engine in which an AI character recognizes a child's emotions. This emotion engine analyzes the child's emotional state based on the child's words, facial expressions, tone of voice, and so on. For example, if a child says, "Today was fun," the emotion engine determines from that statement that the child is feeling joy. Similarly, if a child cries and says, "I can't take it anymore," the emotion engine determines from that statement and the crying that the child is feeling sadness or anger.

[1110] "Example 2"

[1111] Furthermore, the emotion engine adjusts the AI ​​character's response according to the child's emotional state. For example, if the AI ​​character determines that the child is feeling happy, it will offer pleasant conversations to the child. On the other hand, if the AI ​​character determines that the child is feeling sad or angry, it will respond empathetically to the child. This allows the AI ​​character to engage in dialogue that is adapted to the child's emotional state.

[1112] "Example 3"

[1113] The emotion engine also notifies parents of their child's emotional state. For example, if the emotion engine determines that a child is feeling sad or angry, it notifies the parent of that information. This allows parents to understand their child's emotional state and take appropriate action.

[1114] The processing flow of each embodiment will be described below.

[1115] "Example 1"

[1116] Step 1: The AI ​​character initiates a dialogue with the child.

[1117] Step 2: The emotion engine analyzes the child's emotional state based on their words, facial expressions, tone of voice, etc.

[1118] Step 3: The emotion engine communicates the analysis results to the AI ​​character.

[1119] "Example 2"

[1120] Step 1: The emotion engine determines the child's emotional state.

[1121] Step 2: The emotion engine issues instructions to adjust the AI ​​character's response based on the judgment results.

[1122] Step 3: The AI ​​character adjusts its dialogue to the child according to the instructions.

[1123] "Example 3"

[1124] Step 1: The emotion engine determines the child's emotional state.

[1125] Step 2: The emotion engine notifies the parent about the child's emotional state.

[1126] Step 3: Parents receive notifications and are aware of their child's emotional state.

[1127] Example 1

[1128] Next, a description will be given of Example 1 of Form 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."

[1129] Today's children often experience stress in various environments, such as at school and at home. However, it is difficult for children themselves to recognize this stress and deal with it appropriately. It is also difficult for parents and educators to accurately understand a child's stress level and take appropriate measures. Therefore, there is a need for a system that regularly checks children's mental health, identifies the causes of stress, and provides appropriate advice.

[1130] 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.

[1131] In this invention, the server is installed in a device for children and includes an artificial intelligence character that performs regular stress checks, means for identifying the child's mental health condition and stress factors through conversation with the child, means for notifying the parents of the results and providing advice, means for collecting data such as the child's comments, facial expressions, and tone of voice, means including an emotion engine for analyzing the collected data, and means for identifying the child's stress factors based on the analysis results. This makes it possible to accurately grasp the child's mental health condition and take appropriate measures.

[1132] A "child-directed device" is an electronic device designed for use by children.

[1133] "Regular stress checks" are the process of assessing a child's stress level at regular intervals.

[1134] An "artificial intelligence character" is a virtual character that interacts with children using artificial intelligence technology.

[1135] "Children's mental health" refers to the state of a child's mental and emotional health.

[1136] "Stressors" refer to the causes and situations that cause children to feel stressed.

[1137] "Means of notifying parents of results and giving advice" refers to the function of informing parents of the results of their child's stress state and suggesting appropriate ways to respond.

[1138] "Means for collecting data such as a child's statements, facial expressions, and tone of voice" refers to functions for obtaining information such as a child's words, facial expressions, and tone of voice.

[1139] An "emotion engine" is software or algorithms that analyze collected data and determine a child's emotional state.

[1140] "Means for identifying children's stress factors based on analysis results" refers to a function that uses the analysis results of the emotion engine to identify the specific causes of stress in children.

[1141] MODE FOR CARRYING OUT THE INVENTION

[1142] This invention is a system that uses an AI character installed on a device for children to check a child's mental health and identify the causes of stress. A specific embodiment of this system will be described below.

[1143] System configuration

[1144] The system consists of the following major components:

[1145] 1. Child-directed devices: Electronic devices designed for use by children, including hardware such as microphones, cameras, and speakers.

[1146] 2. Artificial Intelligence Character: A virtual character that interacts with children and uses natural language processing (NLP) technology to conduct conversations.

[1147] 3. Emotion engine: Software that analyzes data such as a child's speech, facial expressions, and tone of voice to determine their emotional state. Specifically, it uses Google Cloud Natural Language API and IBM Watson Tone Analyzer.

[1148] 4. Server: A central processing unit for analyzing the collected data and feeding back the results.

[1149] System Operation

[1150] The device initiates a conversation when the child speaks to the AI ​​character. For example, if the child says "Hello," the AI ​​character responds with "Hello, how was your day?" During this conversation, the device collects data such as the child's remarks, facial expressions, and tone of voice.

[1151] The collected data is sent from the device to a server. The server uses an emotion engine to analyze the data and determine the child's emotional state. For example, if a child says, "Today was fun," the emotion engine will determine from that statement that the child is feeling joy. If a child cries and says, "I can't take it anymore," the emotion engine will determine from that statement and the crying that the child is feeling sadness or anger.

[1152] The analysis results are fed back from the server to the device. The device then provides the feedback to the child through an AI character. For example, if the analysis result is "joy," the AI ​​character will respond, "You had fun today. What did you do?" If the analysis result is "sadness" or "anger," the AI ​​character will respond, "What's wrong? Did something happen?"

[1153] Furthermore, the server will identify the child's stressors based on the analysis results. For example, if a child avoids talking about school, it will determine that the child is experiencing school-related stress. This information will be notified to the parents, and appropriate advice will be provided.

[1154] Examples and prompts

[1155] Below are some specific examples and examples of prompts to input to the generative AI model.

[1156] Example 1: When a child says, "Today was fun," the device collects the statement and sends it to the server. The server's emotion engine analyzes it and determines that the child is feeling happy. The device responds through an AI character, "Today was fun, what did you do?"

[1157] Example 2: If a child cries and says, "I can't take it anymore," the device will collect the words and the crying and send them to the server. The server's emotion engine will analyze the data and determine that the child is feeling sad or angry. The device will respond through an AI character, asking, "What's wrong? Did something happen?"

[1158] Example prompt sentence:

[1159] "What stressors might be causing your child to avoid talking about school?"

[1160] "If a child says, 'I had fun today,' how does the emotion engine parse that?"

[1161] In this way, users can understand the operation of the system and utilize it appropriately.

[1162] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1163] Step 1:

[1164] The device starts a conversation by having the child speak to the AI ​​character. The user (child) might say, for example, "Hello." Based on this input, the device collects voice data, and the AI ​​character responds with, "Hello, how was your day?" In this step, voice data collection and an initial response are performed.

[1165] Step 2:

[1166] The device collects data such as the child's remarks, facial expressions, and tone of voice. Specifically, it records audio with a microphone and captures facial expressions with a camera. For example, if a child says, "Today was fun," the audio data and facial expression data are collected. In this step, audio data and video data are collected.

[1167] Step 3:

[1168] The device sends the collected data to the server. The data is encrypted and sent securely. For example, voice data and facial expression data are sent to the server. In this step, data is sent and encrypted.

[1169] Step 4:

[1170] The server analyzes the received data and uses an emotion engine to analyze the child's emotional state. Specifically, it uses software such as Google Cloud Natural Language API and IBM Watson Tone Analyzer. For example, it analyzes the voice data to determine whether the child is feeling "fun." In this step, data analysis and emotional state determination are performed.

[1171] Step 5:

[1172] The server feeds back the analysis results to the device. The device then provides feedback to the child through the AI ​​character. For example, if the analysis result is "joy," the AI ​​character responds, "You had fun today. What did you do?" In this step, the analysis results are fed back and a response is generated.

[1173] Step 6:

[1174] The server identifies the child's stressors based on the analysis results. For example, if a child avoids talking about school, it is determined that the child is experiencing stress related to school. This information is then notified to the parent, who can provide appropriate advice. In this step, the stressors are identified and notified to the parent.

[1175] (Application example 1)

[1176] Next, a description will be given of Application Example 1 of Form 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."

[1177] In modern society, it is important to identify children's mental health conditions and stressors early and respond appropriately. However, it is difficult for parents and educators to accurately grasp children's emotional states and stressors, and these are often overlooked. Furthermore, children themselves are often unable to express their emotions and stress appropriately. This puts children at risk of developing poor mental health.

[1178] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server is installed in a device for children and includes an AI character that performs regular stress checks, means for identifying a child's mental health condition and stress factors through conversation with the child, means for notifying the parents of the results and providing advice, means including an emotion engine that recognizes the child's emotional state by analyzing the child's words, facial expressions, and tone of voice, and means for storing the child's emotional state and stress factors in a database and performing long-term analysis. This makes it possible to identify a child's mental health condition and stress factors early and take appropriate measures.

[1179] A "child-oriented device" is an electronic device designed for everyday use by children.

[1180] "Regular stress checks" are the process of assessing a child's stress level at regular intervals.

[1181] An "AI character" is a virtual character equipped with artificial intelligence that collects and analyzes information by interacting with children.

[1182] "Conversation with a child" refers to the act of a child communicating with an AI character through voice or text.

[1183] "Mental health" refers to a child's mental stability and sense of well-being.

[1184] A "stressor" is a cause or situation that causes stress to a child.

[1185] "Means of notifying parents of results and giving advice" refers to a function that informs parents of their child's mental health status and stress factors and suggests appropriate responses.

[1186] The "Emotion Engine" is an artificial intelligence technology that analyzes a child's words, facial expressions, and tone of voice to recognize their emotional state.

[1187] A "database" is a system for storing and managing information about a child's emotional state and stressors.

[1188] "Longitudinal analysis" is the process of using collected data to assess changes in children's mental health and stressors over time.

[1189] The system for implementing this invention is centered around an AI character installed on a device for children. The system identifies mental health conditions and stress factors through conversations with children, and has the function of notifying parents of the results and providing advice. It also uses an emotion engine to analyze the child's words, facial expressions, and tone of voice to recognize their emotional state.

[1190] Hardware and Software Configuration

[1191] Hardware: Children's devices such as smartphones, smart glasses, and head-mounted displays.

[1192] Software: Python, TensorFlow, database management system (e.g. MySQL).

[1193] Data processing and calculation

[1194] 1. Data collection: The device collects conversation data (voice, text) with the child, facial expression data (camera), and tone of voice data (microphone).

[1195] 2. Data preprocessing: The collected data is converted into text data and then converted into numerical data using a tokenizer.

[1196] 3. Emotion Recognition: The emotion engine uses a Long Short-Term Memory (LSTM) network to analyze a child's speech, facial expressions, and tone of voice to recognize their emotional state.

[1197] 4. Identifying stressors: Identify stressors from the conversation and notify parents if necessary.

[1198] 5. Data storage and analysis: Children's emotional states and stress factors are stored in a database for long-term analysis.

[1199] Specific examples

[1200] For example, if a child says, "Today was fun," the emotion engine will judge the statement as "Positive." If a child says, "I can't take it anymore," while crying, the emotion engine will judge the statement and the crying as "Negative."

[1201] Prompt Sentence Examples

[1202] An example of a prompt to input to a generative AI model is as follows:

[1203] If your child says, "Today was fun," try to recognize the emotion in this statement.

[1204] This system will enable early identification of children's mental health conditions and stressors, allowing appropriate responses, enabling parents and educators to accurately understand their children's emotional state and provide the necessary support.

[1205] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1206] Step 1:

[1207] The device collects conversation data (voice, text), facial expression data (camera), and tone of voice data (microphone). The input is the child's words, facial expressions, and tone of voice, and the output is the collection of this data. Specifically, the device's microphone and camera are used to acquire data in real time.

[1208] Step 2:

[1209] The terminal converts the collected data into text data and then converts it into numerical data using a tokenizer. The input is voice data and text data, and the output is numerical data. Specifically, the terminal uses voice recognition software to convert voice into text, and then uses a tokenizer to convert the text into numerical data.

[1210] Step 3:

[1211] The server uses an emotion engine to analyze the numerical data and recognize the child's emotional state. The input is numerical data, and the output is the recognition result of the emotional state. Specifically, it analyzes the data using an LSTM (Long Short-Term Memory) network and determines the emotional state as "Positive" or "Negative."

[1212] Step 4:

[1213] The server identifies stress factors from the conversation content and notifies parents as necessary. The input is the recognition result of the emotional state and the conversation content, and the output is the identification and notification of stress factors. Specifically, it analyzes the conversation content using natural language processing technology and extracts stress factors.

[1214] Step 5:

[1215] The server stores the child's emotional state and stress factors in a database and performs long-term analysis. The input is the recognition results of the emotional state and stress factors, and the output is the database storage and analysis results. Specifically, the system uses a database management system (e.g., MySQL) to store the data and periodically analyzes it.

[1216] Step 6:

[1217] Parents receive notifications from the server and take appropriate action based on their child's mental health and stressors. The input is the notification from the server, and the output is the parent's response. Specifically, parents check the notification using a smartphone or computer and provide the necessary support.

[1218] Example 2

[1219] Next, a description will be given of Example 2 of Form 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."

[1220] Conventional devices for children lack systems that can properly analyze a child's emotional state and stress factors and provide notifications and advice to parents based on that analysis. This makes it difficult to understand a child's mental health in real time and take appropriate action.

[1221] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for analyzing the emotional state of the child, a means for adjusting the response of the AI ​​character based on the analysis result, a means for generating dialogue content using a generative AI model, and a means for sending a notification to the parent's terminal. This makes it possible to analyze the emotional state of the child in real time and take appropriate action. In addition, it is possible to quickly provide notifications and advice to the parent, thereby effectively supporting the child's mental health.

[1222] A "child-directed device" is an electronic device designed for use by children, including tablets and smartphones.

[1223] An "artificial intelligence character" is a virtual character programmed to analyze a child's emotions and stress levels through dialogue with them and respond appropriately.

[1224] "Emotional state" refers to a child's psychological state and includes emotions such as joy, sadness, and anger.

[1225] An "emotion analysis engine" is a software or hardware system that analyzes a child's facial expressions and tone of voice to identify their emotional state.

[1226] A "generative AI model" is an artificial intelligence model for generating natural language dialogue content based on an input prompt sentence.

[1227] "Dialogue content" refers to the words and phrases used by the AI ​​character in dialogue with the child.

[1228] "Parent device" means an electronic device designed for parental use, including smartphones and tablets.

[1229] "Notifications" are messages that inform parents about their child's emotional state and stressors.

[1230] "Advice" is a suggestion to provide parents with specific ways to deal with their child's emotional state or stressors.

[1231] This invention is a system installed in a device for children that provides an AI character that analyzes the emotional state of a child and responds appropriately based on that analysis. It also notifies parents of information about their child's emotional state and problems, and provides appropriate advice.

[1232] Hardware and software used

[1233] Hardware: Devices used by children (tablets and smartphones), smartphones used by parents

[1234] Software: Sentiment analysis engine, notification system, generative AI model

[1235] Data processing and calculation

[1236] 1. Emotion analysis:

[1237] The device uses a camera and microphone to capture the child's facial expressions and tone of voice in real time.

[1238] The device sends the captured data to an emotion analysis engine.

[1239] The emotion analysis engine uses machine learning models to analyze a child's emotional state, for example identifying emotions such as joy, sadness, or anger from facial expressions.

[1240] The emotion analysis engine sends the analysis results back to the device.

[1241] 2. AI character support:

[1242] The device determines the AI ​​character's response based on the emotional state received from the emotion analysis engine.

[1243] The device uses the generative AI model to generate dialogue based on the child's emotional state. For example, if a child is sad, the AI ​​character will respond empathetically, asking, "What's wrong? Did something happen?"

[1244] The device displays the generated dialogue on the AI ​​character and begins a dialogue with the child.

[1245] 3. Parental Notification and Advice:

[1246] The device sends information about the child's emotional state and problems to a server.

[1247] The server generates a notification to the parent based on the information it receives. For example, if a child is having trouble with friends at school, it generates a notification suggesting that the parent try to communicate with the child or seek professional help.

[1248] The server generates a notification and sends it to the parent's smartphone.

[1249] The parent's smartphone receives the notification and displays it to the parent.

[1250] Specific examples

[1251] Analysis of children's emotional state:

[1252] The device captures the child's face with a camera and records their voice with a microphone.

[1253] The device sends the captured data to an emotion analysis engine.

[1254] The emotion analysis engine determines that the child is sad and sends the result back to the device.

[1255] AI character support:

[1256] The device receives the analysis result that "the child is sad" and sends a prompt to the generative AI model.

[1257] The generative AI model generates the dialogue, "What's wrong? Is something wrong?"

[1258] The device displays the generated dialogue on an AI character, which responds empathetically to the child.

[1259] Parental Notice and Advice:

[1260] The device sends information to the server that "my child is having trouble with friendships at school."

[1261] The server generates a notification that says, "Your child appears to be having trouble with friendships at school. We recommend that you try to communicate with them or seek professional help."

[1262] The server generates a notification and sends it to the parent's smartphone.

[1263] The parent's smartphone receives the notification and displays it to the parent.

[1264] Prompt Sentence Examples

[1265] "If your child is struggling with friendships at school, generate a notification suggesting parents try to have a dialogue or seek professional help."

[1266] This system allows appropriate responses based on a child's emotional state, allowing parents to deal with their child's problems quickly.

[1267] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1268] Step 1:

[1269] The device uses a camera and microphone to capture the child's facial expressions and tone of voice in real time. The input is a video of the child's face and voice, and the output is these data. Specifically, the device's camera captures a picture of the child's face, and the microphone records the child's voice.

[1270] Step 2:

[1271] The device sends the captured data to the emotion analysis engine. The input is the facial video and voice data obtained in step 1, and the output is sending the data to the emotion analysis engine. Specifically, the device uploads the data to the emotion analysis engine via the network.

[1272] Step 3:

[1273] The emotion analysis engine uses a machine learning model to analyze the child's emotional state. The input is the facial video and voice data sent in step 2, and the output is the analysis result. Specifically, the emotion analysis engine analyzes facial expressions and voice tone to identify emotions such as joy, sadness, and anger.

[1274] Step 4:

[1275] The emotion analysis engine returns the analysis results to the terminal. The input is the analysis results obtained in step 3, and the output is data transmission to the terminal. Specifically, the emotion analysis engine sends the analysis results to the terminal via the network.

[1276] Step 5:

[1277] The device determines the AI ​​character's response based on the emotional state received from the emotion analysis engine. The input is the analysis result obtained in step 4, and the output is the AI ​​character's response. Specifically, the device analyzes the analysis result and selects an appropriate response.

[1278] Step 6:

[1279] The device uses the generative AI model to generate dialogue content that corresponds to the child's emotional state. The input is the response content and prompt determined in step 5, and the output is the generated dialogue content. Specifically, the device sends the prompt to the generative AI model to generate dialogue content. For example, the prompt could be "If the child is sad, generate an empathetic response."

[1280] Step 7:

[1281] The device displays the generated dialogue content on the AI ​​character and begins a dialogue with the child. The input is the dialogue content generated in step 6, and the output is the dialogue display of the AI ​​character. Specifically, the device displays the dialogue content on the AI ​​character and responds empathetically to the child, asking, "What's wrong? Is something wrong?"

[1282] Step 8:

[1283] The device sends information about the child's emotional state and problems to the server. The input is data about the child's emotional state and problems, and the output is sending data to the server. Specifically, the device uploads the data to the server via the network.

[1284] Step 9:

[1285] The server generates a notification for the parent based on the information it receives. The input is the data sent in step 8, and the output is the notification content. Specifically, the server generates the notification content based on the child's emotional state and problems. For example, it generates a notification that reads, "Your child appears to be having trouble with friendships at school. We recommend that you try to communicate with them or seek professional help."

[1286] Step 10:

[1287] The server sends the generated notification to the parent's smartphone. The input is the notification content generated in step 9, and the output is the notification sent to the parent's smartphone. Specifically, the server sends the notification to the parent's smartphone via the network.

[1288] Step 11:

[1289] The parent's smartphone receives the notification and displays it to the parent. The input is the notification content sent in step 10, and the output is the display of the notification. Specifically, the parent's smartphone receives the notification and displays a message to the parent saying, "It appears that your child is having trouble with friendships at school. We recommend that you try to communicate with them or seek professional help."

[1290] (Application example 2)

[1291] Next, a description will be given of Application Example 2 of Form 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."

[1292] Today's children face difficulties receiving appropriate support for dealing with stress and emotional fluctuations at school and at home. Parents, in particular, are required to quickly understand their children's emotional state and stress factors and respond appropriately. However, conventional methods have had difficulty analyzing children's emotional state in real time and providing specific advice to parents.

[1293] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1294] In this invention, the server is installed in a device for children and includes an AI character that performs regular stress checks, means for identifying the child's mental health condition and stress factors through conversation with the child, means for notifying the parents of the results and giving them advice, means for analyzing the child's emotional state in real time, means for taking appropriate action based on the analysis results, and means for providing specific advice to the parents. This enables parents to grasp the child's emotional state in real time and respond promptly and appropriately.

[1295] "Children's devices" are electronic devices intended for use by children, including smartphones, tablets, and smart glasses.

[1296] "Regular stress check" is the process of assessing a child's stress level at regular intervals.

[1297] An "AI character" is a virtual character equipped with artificial intelligence that has the ability to analyze a child's emotions and stress levels through dialogue with them.

[1298] "Methods for identifying a child's mental health condition and stress factors through conversations with the child" refers to a method for having a conversation with a child and identifying the child's mental health condition and stress factors from the content of the conversation.

[1299] "Means of informing parents of results and providing advice" refers to methods for informing parents of their child's emotional state and stress factors and suggesting appropriate ways of responding.

[1300] "Means for analyzing a child's emotional state in real time" refers to a method for instantly assessing a child's emotions and taking appropriate action based on the results.

[1301] "Means for taking appropriate action based on the analysis results" refers to a method for engaging in appropriate dialogue or taking appropriate action toward a child based on the results of emotion analysis.

[1302] "Means for providing specific advice to parents" are methods for suggesting specific ways of responding to parents based on their child's emotional state and stress factors.

[1303] The embodiments of the present invention will be described in detail below.

[1304] System Overview

[1305] The system is centered around an AI character installed on children's devices. The devices are electronic devices such as smartphones, tablets, and smart glasses. The AI ​​character identifies the child's emotional state and stress factors through dialogue with the child and notifies the parents of the results. It also takes appropriate action based on the analysis results and provides specific advice to the parents.

[1306] Hardware and software used

[1307] Hardware: Smartphones, tablets, smart glasses

[1308] Software: Python, virtual emotion engine library (EmotionEngine), virtual AI character library (AICharacter), SMTP library

[1309] Data processing and calculation

[1310] 1. Emotion Analysis: The device uses an emotion engine (Emotion Engine) to analyze the child's emotional state in real time. The emotion engine analyzes the child's facial expressions, tone of voice, and the content of the conversation to identify their emotional state.

[1311] 2. Response Generation: Based on the results of emotion analysis, the AI ​​Character generates an appropriate response. For example, if the child is sad, it will engage in empathetic dialogue, and if the child is happy, it will offer a pleasant topic.

[1312] 3. Notification and Advice: Parents are notified of the results of the emotion analysis and the appropriate response. The SMTP library is used to send a notification via email to the parent's smartphone. The notification includes specific advice based on the child's emotional state and stressors.

[1313] Specific examples

[1314] For example, if a child is having trouble making friends at school, the emotion engine will identify their emotional state as "sad." The AI ​​character will then engage in empathetic dialogue with the child and advise the parents, "Your child is having trouble making friends at school. Please try to talk to them or seek professional help."

[1315] Prompt Sentence Examples

[1316] "What advice would you offer parents if their child is struggling with friendships at school?"

[1317] In this way, the system can understand the child's emotional state in real time, allowing parents to respond quickly and appropriately.

[1318] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1319] Step 1:

[1320] The device launches an emotion engine (Emotion Engine) to analyze the child's emotional state in real time. As input, it receives data such as the child's facial expressions, tone of voice, and dialogue content. The emotion engine analyzes this data and identifies the child's emotional state (e.g., joy, sadness, anger, etc.). As output, it generates the identified emotional state.

[1321] Step 2:

[1322] The device launches an AI character (AICharacter) based on the emotional state obtained from the emotion engine. The identified emotional state is passed to the AICharacter as input. The AICharacter generates an appropriate response (e.g., empathetic dialogue or providing a fun topic) according to the emotional state. The generated response is output.

[1323] Step 3:

[1324] The device executes the generated response content against the child. As input, it receives the response content from the AI ​​character. The device executes the generated response content through dialogue with the child and observes the child's reaction. As output, it generates the child's reaction data.

[1325] Step 4:

[1326] The device notifies the parent based on the child's emotional state and stress factors. As input, it receives emotional state data from the emotion engine and response data from the AI ​​character. The device uses an SMTP library to send a notification via email to the parent's smartphone. The notification includes specific advice based on the child's emotional state and stress factors. As output, it generates the sent notification data.

[1327] Step 5:

[1328] The parent receives the notification from the device and checks the advice based on the child's emotional state and stress factors. The notification data from the device is acquired as input. The parent responds appropriately to the child based on the notification content. The parent's response action is generated as output.

[1329] In this way, the system can understand the child's emotional state in real time, allowing parents to respond quickly and appropriately.

[1330] Example 3

[1331] Next, a description will be given of Example 3 of Form Example 3. 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."

[1332] Today's children often find it difficult to receive appropriate support for dealing with stress and emotional fluctuations at school and at home. A particularly serious problem is the inability of parents to grasp their children's emotional state in real time and respond appropriately. Therefore, there is a need for a system that can accurately analyze a child's emotional state and quickly notify parents.

[1333] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1334] In this invention, the server includes means for analyzing the content, tone, and facial expressions of the child's speech, means for identifying the child's emotional state by integrating the analysis results, and means for notifying the parent of the identified emotional state. This makes it possible to analyze the child's emotional state in real time and promptly notify the parent.

[1335] The "artificial intelligence character" is a program that analyzes a child's emotional state and stress factors through dialogue with them.

[1336] "Children's mental health status" refers to the emotional and stress levels a child is experiencing.

[1337] A "stressor" is an event or situation that causes stress to a child.

[1338] "Means for notifying parents of the results" refers to a method for informing parents of the analyzed emotional state and stress factors of their child.

[1339] "Advice tools" are methods that suggest appropriate responses to parents based on their child's emotional state and stressors.

[1340] "Methods for analyzing the content, tone, and facial expressions of speech" are methods for identifying a child's emotional state by analyzing the content of speech, tone of voice, and facial expressions.

[1341] The "means for integrating analysis results" refers to a method for identifying a child's emotional state by combining the results of voice analysis and facial expression analysis.

[1342] "Means for identifying emotional states" refers to methods for clarifying a child's emotional state based on the analyzed data.

[1343] A "parental notification method" is a method for informing a parent of an identified emotional state.

[1344] The present invention provides a system for analyzing a child's emotional state and notifying the parent of the results. The system includes a child-oriented terminal, a server, and a parent's terminal. Specific embodiments are described below.

[1345] Hardware and software used

[1346] Hardware: Camera, microphone, server, parent device (smartphone or PC)

[1347] Software: voice recognition software (e.g., voice recognition API), facial expression recognition software (e.g., facial expression recognition API), sentiment analysis engine (e.g., sentiment analysis API)

[1348] System configuration

[1349] 1. Device:

[1350] The device is equipped with a camera and microphone to collect the child's facial expressions and comments in real time.

[1351] For example, a child might say, "Something bad happened at school today," and the camera would capture their facial expression.

[1352] 2. Server:

[1353] The server converts the voice data sent from the terminal into text using a voice recognition API.

[1354] The converted text data is sent to the sentiment analysis API for sentiment analysis.

[1355] The server sends the video data obtained from the camera to an facial expression recognition API, which analyzes emotions from facial expressions.

[1356] For example, if the result of voice analysis is "sadness" and the result of facial expression analysis is "anger," these pieces of information are integrated.

[1357] The server integrates the results of voice analysis and facial expression analysis to identify the child's emotional state.

[1358] For example, if "sadness" and "anger" are detected at the same time, "events at school" will be identified as a stressor.

[1359] 3. Parent device:

[1360] The emotion engine notifies the parent of the identified emotional state.

[1361] Parents receive notifications via their smartphones or PCs to understand their children's emotional state.

[1362] For example, you might receive a notification that says, "Your child has had a bad experience at school. We are feeling sad and angry."

[1363] Specific examples

[1364] If a child says, "My friends ignored me today," audio and facial expressions are collected.

[1365] "Sadness" is detected through voice analysis, and "anger" is detected through facial expression analysis.

[1366] The emotion engine identifies "being ignored by friends" as the cause of stress and notifies the parents.

[1367] Prompt Sentence Examples

[1368] "Please explain the system that analyzes a child's voice and facial expressions when they say something bad happened at school and notifies the parent of their emotional state."

[1369] This system allows parents to understand their child's emotional state in real time and take appropriate action. The flow of the identification process in the third embodiment will be described with reference to FIG.

[1370] Step 1:

[1371] Data collection

[1372] The device uses a camera and microphone to collect the child's facial expressions and speech in real time.

[1373] Input: Child's speech and facial expression video

[1374] Specific actions: For example, a child says, "Something bad happened at school today," and the camera captures their facial expression.

[1375] Output: Audio and video data are generated and sent to the server.

[1376] Step 2:

[1377] Converting audio data to text

[1378] The server converts the received voice data into text using a voice recognition API.

[1379] Input: Audio data

[1380] Specific operation: The server calls the speech recognition API and converts the voice data into text.

[1381] Output: The converted text data (e.g. "Something bad happened at school today")

[1382] Step 3:

[1383] Sentiment analysis of voice data

[1384] The server sends the converted text data to the sentiment analysis API for sentiment analysis.

[1385] Input: Text data

[1386] Specific operation: The server calls the sentiment analysis API and analyzes the text data.

[1387] Output: Sentiment analysis result (e.g. "sadness")

[1388] Step 4:

[1389] Emotion analysis of facial expression data

[1390] The server sends the received video data to an facial expression recognition API, which analyzes emotions from facial expressions.

[1391] Input: Video data

[1392] Specific operation: The server calls the facial expression recognition API and analyzes the video data.

[1393] Output: Facial expression analysis result (e.g. "Anger")

[1394] Step 5:

[1395] Integrating and identifying emotional states

[1396] The server integrates the results of voice analysis and facial expression analysis to identify the child's emotional state.

[1397] Input: Voice analysis results and facial expression analysis results

[1398] Specific operation: The server integrates the voice analysis result "sadness" and the facial expression analysis result "anger."

[1399] Output: Integrated emotional state (e.g., "What happened at school is stressful for me")

[1400] Step 6:

[1401] Parental Notification

[1402] The emotion engine notifies the parent of the identified emotional state.

[1403] Input: Integrated emotional state

[1404] Specific operation: The emotion engine generates a notification message and sends it to the parent's smartphone or PC.

[1405] Output: Parent notification message (e.g., "Your child has had a bad experience at school. We are feeling sad and angry.")

[1406] (Application example 3)

[1407] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[1408] In modern society, it is important to identify children's mental health conditions and stressors early and take appropriate measures. However, it is difficult for parents to understand their children's emotional state in real time, which can lead to overlooking problems they may be experiencing. In addition, there is a lack of systems that accurately analyze children's emotional states and notify parents, making it difficult for parents to take appropriate measures.

[1409] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server is installed in a terminal for children and includes an AI character that performs regular stress checks, means for identifying the child's mental health condition and stress factors through conversation with the child, means for notifying the results and giving advice to the parents, means for analyzing the child's facial expressions and tone of voice, and means for notifying the parents based on the analysis results. This enables parents to understand the child's emotional state in real time and take appropriate action.

[1410] A "child-directed device" is an electronic device designed for use by children.

[1411] "Regular stress checks" are the process of assessing a child's stress levels at regular intervals.

[1412] An "AI character" is a virtual character equipped with artificial intelligence that has the ability to interact with children.

[1413] "Conversation with a child" refers to the act of exchanging information between a child and an AI character through voice or text.

[1414] "Mental health" refers to a child's mental stability and sense of well-being.

[1415] A "stressor" is a cause or situation that causes stress to a child.

[1416] "Parent notification" refers to the act of communicating information about a child's emotional state and stressors to parents.

[1417] "Advice tools" are ways of suggesting appropriate actions or measures to children and parents.

[1418] "Means for analyzing a child's facial expressions and tone of voice" refers to technology that uses a camera and microphone to analyze a child's facial expressions and tone of voice.

[1419] "Means for notifying parents based on the analysis results" refers to a method for conveying information to parents based on the analyzed data.

[1420] The system for implementing this invention is installed in a device for children. The device includes an AI character that performs regular stress checks and has a means for identifying mental health conditions and stress factors through conversations with the child. It also includes a means for notifying parents of the results and providing advice.

[1421] Hardware and software used

[1422] Hardware: Smartphone camera and microphone

[1423] Software: OpenCV, Keras, SpeechRecognition, smtplib

[1424] System processing overview

[1425] 1. Initialize the camera:

[1426] The device's camera is initialized using OpenCV and the child's facial expressions are captured in real time.

[1427] 2. Emotion recognition:

[1428] The video frames acquired from the camera are converted to grayscale and face detection is performed. The detected face regions are input into an emotion recognition model (using Keras) to predict emotions.

[1429] 3. Speech Recognition:

[1430] The SpeechRecognition library is used to convert the audio captured from the microphone into text, which allows us to analyze what the child is saying.

[1431] 4. Notice:

[1432] If the emotion is "anger" or "sadness," the parent is notified by email. The email contains the emotional state and the content of the message. SMTPlib is used to send the email.

[1433] Specific examples

[1434] For example, if a child shows an angry expression in front of the camera and says, "I've had enough!", the system will recognize that emotion as "anger" and send the parent an email stating, "Child's emotional state: anger\nStatement: I've had enough!"

[1435] Prompt Sentence Examples

[1436] Develop an application that analyzes a child's emotional state in real time and notifies parents. Using the smartphone's camera and microphone, the application analyzes the child's facial expressions and tone of voice, and the emotion engine identifies stressors. Parents can understand their child's emotional state through the app and take appropriate action. The libraries used are OpenCV, Keras, SpeechRecognition, and smtplib.

[1437] In this way, a system can be realized that allows parents to grasp their child's emotional state in real time and take appropriate action.

[1438] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1439] Step 1:

[1440] The device initializes the camera using OpenCV, acquires video frames from the camera in real time, and captures the child's facial expressions. The input is the video frame from the camera, and the output is the captured video frame.

[1441] Step 2:

[1442] The device converts the captured video frame to grayscale, and then uses the OpenCV face detection algorithm to perform face detection. The input is the captured video frame, and the output is the detected face area.

[1443] Step 3:

[1444] The device preprocesses the detected face region to input it into the emotion recognition model. Specifically, the face region is resized to 48x48 pixels and normalized. The input is the detected face region, and the output is the preprocessed face image data.

[1445] Step 4:

[1446] The device inputs the preprocessed facial image data into an emotion recognition model built using Keras. The model predicts emotions from the facial image data. The input is the preprocessed facial image data, and the output is the predicted emotion.

[1447] Step 5:

[1448] The device analyzes the prediction results of the emotion recognition model and identifies the emotion with the highest probability. The input is the emotion prediction result, and the output is the identified emotion (e.g., anger, sadness).

[1449] Step 6:

[1450] The device uses the SpeechRecognition library to capture audio from the microphone and convert it to text. The input is the audio data from the microphone, and the output is the speech converted to text.

[1451] Step 7:

[1452] The device generates a message to notify the parent based on the identified emotion and the speech content converted into text. The input is the identified emotion and speech content, and the output is the notification message.

[1453] Step 8:

[1454] The terminal uses smtplib to generate and email notification messages to the parent. The input is the notification message and the output is the email sent.

[1455] In this way, the device will be able to analyze the child's emotional state in real time and notify the parents.

[1456] 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.

[1457] 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> ) 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.

[1458] Another example of generative AI is Gemini (internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1459] 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.

[1460] [Third embodiment]

[1461] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1462] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1463] 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).

[1464] 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.

[1465] 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.

[1466] 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).

[1467] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for 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.

[1468] 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.

[1469] 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.

[1470] 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.

[1471] 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.

[1472] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1473] "Example 1"

[1474] In one embodiment of the present invention, an AI character installed on a device for children conducts stress checks through conversations with the child. The AI ​​character identifies mental health conditions and stress factors from the child's comments and reactions. For example, if a child avoids talking about school, the AI ​​character can identify school-related stress.

[1475] "Example 2"

[1476] The AI ​​character then notifies the parent of the results and offers advice. The notification is sent to the parent's smartphone using the device's notification function. The advice provides specific solutions to issues that are causing stress to the child. For example, if a child is having trouble with friends at school, the AI ​​character will suggest that the parent try to talk to the child or seek professional help.

[1477] "Example 3"

[1478] The AI ​​character also analyzes the child's emotional state based on the content, tone, and facial expressions of the child's speech. For example, if the child expresses anger or sadness, the AI ​​character analyzes this information and identifies the cause of stress.

[1479] The processing flow of each embodiment will be described below.

[1480] "Example 1"

[1481] Step 1: The AI ​​character initiates a conversation with the child. This conversation can be initiated by the child interacting with the device, or by the AI ​​character periodically prompting the conversation.

[1482] Step 2: The AI ​​character will engage in conversation to explore the child's mental health and stressors, collecting information through questions such as, "How was your day?" and "Did anything interesting happen at school?"

[1483] Step 3: The AI ​​character analyzes the collected information and assesses the child's stress level, using AI natural language processing and machine learning techniques.

[1484] "Example 2"

[1485] Step 1: The AI ​​character notifies the parent of the analysis results. This notification is sent via the device's notification function directly to the parent's smartphone.

[1486] Step 2: The notification will include the child's stress level, its contributing factors, and recommendations. The recommendations will provide specific action plans to reduce the child's stress.

[1487] "Example 3"

[1488] Step 1: The AI ​​character analyzes the child's emotional state based on the content, tone, and facial expressions of the child's speech.

[1489] Step 2: The AI ​​character uses the emotional state analysis results to identify the child's stressors. For example, if the child expresses anger or sadness, the AI ​​character analyzes that information and identifies the stressors.

[1490] Step 3: Based on the identified stressors, the AI ​​character generates advice for the child and parent, providing specific courses of action to reduce the stressors.

[1491] Example 1

[1492] Next, a description will be given of Example 1 of Form 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."

[1493] Today's children are often exposed to stress at school and at home, making it important to properly understand their mental health. However, it is difficult for parents and teachers to accurately understand a child's stress and emotional state, which can delay appropriate responses. Furthermore, children often have difficulty expressing their own stress and emotions effectively. This has led to a need for effective methods to properly manage children's mental health.

[1494] The identification process by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. In this invention, the server is installed in a terminal for children and includes an AI character that performs regular stress checks, a means for identifying the child's mental health state and stress factors through conversation with the child, a means for notifying the results and providing advice to the parent, a means for collecting the child's comments and sending them to the generative AI model, and a means for receiving the analysis results from the generative AI model and providing appropriate feedback and advice to the child. This makes it possible to grasp the child's mental health state in real time and take appropriate measures quickly.

[1495] A "child-directed device" is an electronic device designed for use by children.

[1496] "Regular stress checks" are the process of assessing a child's stress level at regular intervals.

[1497] An "artificial intelligence character" is a virtual character that interacts with children using artificial intelligence technology.

[1498] "Conversation with a child" refers to the act of a child communicating with an AI character through voice or text.

[1499] "Mental health" refers to a child's mental stability and emotional state.

[1500] "Stressors" refer to causes or situations that cause stress to children.

[1501] "Notifying parents of results" refers to the act of communicating information about a child's mental health and stress factors to parents.

[1502] "Advice tools" are methods for providing appropriate advice and instruction to children and parents.

[1503] "Means of collecting statements" refers to the method of recording children's statements and saving them as data.

[1504] A "generative artificial intelligence model" is a model generated using artificial intelligence technology that performs natural language processing and sentiment analysis.

[1505] "Means for receiving analysis results" refers to a method for importing analysis results from a generative artificial intelligence model into a terminal.

[1506] "Means for providing appropriate feedback and advice" refers to methods for providing appropriate responses and advice to children based on the analysis results.

[1507] MODE FOR CARRYING OUT THE INVENTION

[1508] This invention is a system that uses an AI character installed on a device for children to identify a child's mental health condition and stress factors, and notifies the parents of the results and provides advice. A specific embodiment of this system is described below.

[1509] Generating a Program

[1510] The server generates the AI ​​character program to be installed on the device for children. This program uses natural language processing technology to analyze conversations with children and identify their mental health status and stress factors. Specifically, the program is developed using programming languages ​​such as Python and Java and distributed to the device via AWS (Amazon Web Services) or Google Cloud Platform.

[1511] Program processing

[1512] The terminal installs the distributed program and starts the AI ​​character. The user (child) operates the terminal and starts a conversation with the AI ​​character. For example, if the user says "Hello," the AI ​​character will reply, "Hello, how was your day?"

[1513] The device uses a microphone to collect the user's speech. The collected voice data is converted into text in real time and sent to the generative AI model. For example, if a user says, "Nothing fun happened at school today," the text data is sent to the generative AI model.

[1514] The generative AI model analyzes the text data sent. Specifically, it uses generative AI models such as Google's Dialogflow and OpenAI's GPT-3 to identify emotions and stress factors from the user's speech. The analysis results indicate that the user is likely to have negative feelings toward school.

[1515] The device receives the analysis results from the generative AI model. For example, if the device determines that the user has negative feelings about school, it uses voice synthesis technology to provide feedback to the user, such as, "Have you had any problems at school?"

[1516] Examples and prompts

[1517] As a concrete example, the following conversation can be considered:

[1518] User (child): "Nothing fun happened at school today."

[1519] AI character: "Oh yeah. Did you get in trouble at school?"

[1520] From this conversation, the AI ​​character identifies the possibility that the child has negative feelings about school.

[1521] Examples of prompts to be input to a generative AI model include:

[1522] Prompt: "What stressors might be causing your child to avoid talking about school?"

[1523] By inputting this prompt into the generative AI model, the AI ​​character can generate appropriate feedback and advice.

[1524] As described above, this invention is a system that makes it possible to grasp a child's mental health condition in real time and to take appropriate measures quickly.

[1525] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1526] Step 1:

[1527] The server generates programs for AI characters to be installed on children's devices and distributes them to the devices. Specifically, the server develops programs using programming languages ​​such as Python and Java and distributes them to devices via AWS or Google Cloud Platform. The input is the program source code, and the output is a program that can be installed on the device.

[1528] Step 2:

[1529] The terminal installs the distributed program and starts the AI ​​character. The user (child) operates the terminal and starts a conversation with the AI ​​character. Specifically, when the user says "Hello," the AI ​​character replies "Hello, how was your day?" The input is the user's voice, and the output is the AI ​​character's response.

[1530] Step 3:

[1531] The device uses a microphone to collect user speech and converts it into text in real time. The collected speech data is then converted into text using speech recognition technology. The input is the user's speech data, and the output is text data.

[1532] Step 4:

[1533] The device sends the generated text data to the generative AI model. Specifically, the device sends the text data to the generative AI model on the server via the Internet. The input is the text data, and the output is the data sent to the generative AI model.

[1534] Step 5:

[1535] The generative AI model analyzes the submitted text data and identifies mental health conditions and stress factors. Specifically, the generative AI model uses natural language processing technology to analyze the text data and identify emotions and stress factors. The input is the text data, and the output is the analysis results.

[1536] Step 6:

[1537] The device receives the analysis results from the generative AI model and provides appropriate feedback and advice to the user. Specifically, the device uses voice synthesis technology to provide feedback to the user based on the analysis results. For example, if it is determined that the user has negative feelings toward school, the device will provide feedback such as, "Have you had any trouble at school?" The input is the analysis results, and the output is feedback generated for the user.

[1538] Step 7:

[1539] The device notifies the parent of the analysis results and feedback. Specifically, the device sends notifications via the Internet to the parent's smartphone or email address. The inputs are the analysis results and feedback, and the output is a notification to the parent.

[1540] (Application example 1)

[1541] Next, a description will be given of Application Example 1 of Form 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."

[1542] Today's children often experience stress due to various factors, including school and home environments. However, it is difficult for children themselves to recognize this stress and deal with it appropriately. It is also not easy for parents and educators to understand a child's stress level and respond early. Therefore, there is a need for a system that regularly checks children's mental health, identifies stress factors, and provides appropriate advice.

[1543] 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.

[1544] In this invention, the server is installed in a device for children and includes an AI character that performs regular stress checks, means for identifying the child's mental health condition and stress factors through conversation with the child, means for notifying the parents of the results and providing advice, means for using a generative AI model to evaluate the stress level from the child's comments and reactions, means for notifying the parents or experts when the stress level is high, and means for providing regular reports on the child's mental health condition, which makes it possible to detect a child's stress state early and take appropriate measures.

[1545] A "child-directed device" is an electronic device designed for use by children.

[1546] "Regular stress checks" are the process of assessing a child's stress level at regular intervals.

[1547] An "AI character" is a virtual character equipped with artificial intelligence that has the ability to collect and analyze information through dialogue with children.

[1548] "Conversation with a child" refers to the act of exchanging information between a child and an AI character through voice or text.

[1549] "Mental health" refers to a child's mental and emotional stability.

[1550] "Stressors" refer to causes or situations that cause stress to children.

[1551] "Means of notifying parents of results and providing advice" refers to methods for conveying information about their child's stress level and mental health status to parents and encouraging them to take appropriate measures.

[1552] The "generative AI model that assesses stress levels from children's statements and reactions" is an artificial intelligence model that analyzes children's behavior and words and determines the level of stress.

[1553] "Means to notify parents and professionals when stress levels are high" refers to a method to communicate this information to parents and professionals when a child's stress level exceeds a certain threshold.

[1554] "Means for providing regular reports on children's mental health status" refers to a method for regularly compiling information on children's mental health status and reporting it to parents and professionals.

[1555] The system for carrying out this invention is mainly composed of an AI character installed on a device for children. A specific embodiment of this system will be described below.

[1556] System configuration

[1557] The system consists of the following main components:

[1558] 1. Child-directed devices: Electronic devices such as smartphones and tablets used by children.

[1559] 2. AI Character: A virtual character equipped with artificial intelligence that collects and analyzes information through dialogue with children.

[1560] 3. Generative AI model: An artificial intelligence model for assessing stress levels from children's statements and reactions.

[1561] 4. Notification system: A system to notify parents and professionals when stress levels are high.

[1562] 5. Reporting system: A system that provides regular reports on children's mental health status.

[1563] Program processing

[1564] The server does the following:

[1565] 1. Conversation collection: Collect conversations between a child and an AI character in text format. For example, a child might answer "Hmm, nothing in particular" to the question "What did you do at school today?"

[1566] 2. Stress Level Analysis: Using a generative AI model, we assess stress levels from collected conversations. We use OpenAI's API to analyze conversations and determine the level of stress.

[1567] 3. Notification: Notify parents or professionals when stress levels are high, for example, by sending a message saying "Warning: Child's stress level is high."

[1568] 4. Generate reports: Regularly summarize the child's mental health status and provide it as a report to parents and professionals.

[1569] Hardware and software used

[1570] Hardware: smartphones, tablets, servers

[1571] Software: OpenAI API, generative AI models

[1572] Specific examples

[1573] Below are some examples of specific conversations and prompts:

[1574] Example conversation

[1575] AI: What did you do at school today?

[1576] Child: Hmm, nothing in particular.

[1577] AI: Did you hang out with friends?

[1578] Child: No, not really.

[1579] Prompt Sentence Examples

[1580] Assess your child's stress level from the following conversation:

[1581] AI: What did you do at school today?

[1582] Child: Hmm, nothing in particular.

[1583] AI: Did you hang out with friends?

[1584] Child: No, not really.

[1585] evaluation:

[1586] In this way, the system can detect stress in children early and take appropriate measures.

[1587] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1588] Step 1:

[1589] Conversation collection

[1590] The device collects conversations between the child and the AI ​​character in text format. Specifically, when the child speaks to the device, the speech is converted into text and saved as a conversation log. The input is the child's speech, and the output is a text-format conversation log.

[1591] Step 2:

[1592] Stress level analysis

[1593] The server inputs the collected conversation logs into a generative AI model to evaluate stress levels. Specifically, it uses OpenAI's API to analyze the conversation content and determine the degree of stress. The input is a text-format conversation log, and the output is an evaluation result of the stress level.

[1594] Step 3:

[1595] notification

[1596] If the stress level is high, the server notifies the parent or expert. Specifically, based on the stress level assessment result, it sends a message to the parent or expert saying, "Warning: Your child's stress level is high." The input is the stress level assessment result, and the output is the notification message.

[1597] Step 4:

[1598] Generate reports

[1599] The server periodically summarizes the child's mental health status and provides it to parents and specialists as a report. Specifically, it aggregates conversation logs and stress level assessment results over a certain period of time and generates a report. The input is the conversation logs and stress level assessment results over a certain period of time, and the output is a mental health status report.

[1600] Step 5:

[1601] Providing advice

[1602] The server identifies the causes of stress and provides corresponding advice. Specifically, it uses a generative AI model to analyze the causes of stress and generate appropriate advice. The input is the conversation log and the stress level assessment results, and the output is the content of the advice.

[1603] Example 2

[1604] Next, a description will be given of Example 2 of Form 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."

[1605] Today's children are often exposed to stress at school and at home, and it is necessary to detect this stress early and deal with it appropriately. However, it is difficult for parents to accurately grasp their children's stress levels and provide appropriate advice. With conventional methods, there is a lack of a system in place to identify the causes of children's stress and notify parents, making it difficult to protect children's mental health.

[1606] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for transmitting generated data to a cloud server, a means for the cloud server to analyze the stress level using the generated AI model, and a means for the cloud server to generate notification content and advice based on the analysis result. This makes it possible to detect stress in children early and provide appropriate advice to parents.

[1607] The "artificial intelligence character" is a program that is installed on devices for children, conducts regular stress checks, and identifies mental health conditions and stress factors through conversations with children.

[1608] The "cloud server" is a remote server that receives data via the internet, analyzes stress levels using a generative AI model, and generates notifications and advice based on the analysis results.

[1609] A "generative AI model" is an artificial intelligence algorithm that analyzes the received data and assesses a child's stress level.

[1610] The "notification function" is a function that enables the terminal to send notification of results and advice to the parent's information terminal.

[1611] A "stress check" is a process of collecting data on a child's behavior and emotions to assess the presence and level of stress.

[1612] "Analysis results" are information about stress levels and factors that the generative AI model outputs based on input data.

[1613] "Advice" refers to specific solutions or suggestions provided to parents based on the analysis results.

[1614] "Data transmission means" refers to the functions and protocols for transmitting data from the terminal to the cloud server.

[1615] This invention is a system that uses an AI character installed on a device for children to periodically check a child's stress level, notify the parents of the results, and provide appropriate advice. This system is implemented using the following hardware and software.

[1616] Hardware and software used

[1617] Hardware: Smartphones, cloud servers

[1618] Software: Generative AI model, notification function (depending on smartphone OS)

[1619] Specific operation of the system

[1620] 1. The user enters data to measure the child's stress level.

[1621] Users open a smartphone app and answer questions about their child's behavior and emotions.

[1622] Example: A user fills out an app's questionnaire form and responds to the prompt, "Tell us about any recent changes in your child's behavior or emotions" by typing, "He recently had a fight with a friend at school."

[1623] 2. The device sends the entered data to the cloud server.

[1624] When the smartphone app presses the "send" button, the data is uploaded to a cloud server via the Internet.

[1625] 3. The server inputs the received data into a generative AI model to analyze stress levels.

[1626] The server passes the data to a generative AI model implemented in Python, which determines the stress level as "high" based on the information that the user "had a fight with a friend."

[1627] 4. Based on the analysis results, the server identifies the child's stress factors and generates notifications and advice for parents.

[1628] The server generates a message saying, "Your child is having trouble with friendships at school. We suggest you try to communicate with them or seek professional help."

[1629] 5. The server generates notifications and sends advice to the device.

[1630] The server generates a message and sends it to a smartphone app, which receives the message.

[1631] 6. The device uses the notification function to send a notification to the parent's smartphone.

[1632] A notification will appear in the notification bar on your smartphone saying, "We have an important message for you regarding stress in children."

[1633] Prompt Sentence Examples

[1634] "Tell me what problems your child has been having at school recently."

[1635] "Tell me about any recent changes in your child's behavior or emotions."

[1636] This system will enable parents to detect stress in their children early and provide appropriate coping strategies, thereby strengthening support for protecting children's mental health.

[1637] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1638] Step 1:

[1639] The user inputs data to measure the child's stress level.

[1640] Input: A user opens a smartphone app and answers questions about their child's behavior and emotions.

[1641] What happens: A user fills out an app questionnaire prompting them to "Tell us about any recent changes in your child's behavior or emotions," and answers, "They recently had a fight with a friend at school."

[1642] Output: The input data is saved in the smartphone app.

[1643] Step 2:

[1644] The terminal transmits the input data to the cloud server.

[1645] Input: User input data stored in the smartphone app.

[1646] Specific operation: When the smartphone app presses the "send" button, the data is uploaded to a cloud server via the Internet.

[1647] Output: Data is sent to the cloud server.

[1648] Step 3:

[1649] The server inputs the received data into a generative AI model to analyze stress levels.

[1650] Input: User input data sent to the cloud server.

[1651] Specific operation: The server passes data to a generative AI model implemented in Python, which determines the stress level as "high" based on the information that "you had a fight with a friend."

[1652] Output: Stress level analysis results are generated.

[1653] Step 4:

[1654] Based on the analysis results, the server identifies the child's stress factors and generates notifications and advice to be sent to parents.

[1655] Input: Stress level analysis results from a generative AI model.

[1656] Specific behavior: The server generates a message saying, "Your child is having trouble with friendships at school. We suggest you try to communicate with them or seek professional help."

[1657] Output: Notifications and advice are generated.

[1658] Step 5:

[1659] The server generates notifications and advice and sends them to the terminal.

[1660] Input: Generated notification content and advice.

[1661] Specific operation: The server generates a message and sends it to the smartphone app, which then receives the message.

[1662] Output: Notifications and advice are sent to the smartphone app.

[1663] Step 6:

[1664] The device uses the notification function to send a notification to the parent's smartphone.

[1665] Input: Notifications and advice sent by the server.

[1666] What it does: A notification will appear in your smartphone's notification bar saying, "We have an important message for you about your child's stress."

[1667] Output: A notification will appear on the parent's smartphone.

[1668] (Application example 2)

[1669] Next, a description will be given of Application Example 2 of Form 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."

[1670] Today's children often experience stress due to various factors, including school, home, and friendships. However, children themselves are often unable to express their stress appropriately, making it difficult for parents to understand the situation. It is also difficult for parents to understand their children's stressors and find appropriate ways to deal with them. This puts children at risk of developing poor mental health. This invention aims to protect children's mental health by identifying their stressors and providing appropriate advice to parents.

[1671] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server is installed in a terminal for children and includes an AI character that performs regular stress checks, means for identifying the child's mental health condition and stress factors through conversation with the child, means for notifying the results and providing advice to the parent, means for identifying the child's stress factors using a generative AI model, means for generating specific advice for the identified stress factors, and means for sending a notification to the parent's terminal. This makes it possible to quickly and accurately identify the child's stress factors and provide appropriate advice to the parent.

[1672] A "child-directed device" is an electronic device designed for use by children.

[1673] "Regular stress checks" are the process of assessing a child's stress levels at regular intervals.

[1674] An "artificial intelligence character" is a virtual character that uses AI technology to interact with children and analyze their emotions and stress.

[1675] "Children's mental health" refers to a child's mental health and emotional stability.

[1676] "Stressors" refer to the causes and situations that cause children to feel stressed.

[1677] "Means of notifying parents of results and giving advice" refers to methods and functions for informing parents of their child's stress level and how to deal with it.

[1678] A "generative AI model" is a model that has been trained using artificial intelligence to perform a specific task.

[1679] "Specific advice for identified stressors" refers to specific coping strategies or suggestions provided based on the detected causes of stress.

[1680] "Means for sending notifications to parent's terminal" refers to a method or function for sending information to the electronic device used by the parent.

[1681] The system for implementing this invention is composed of a terminal for children, a server, and a terminal for parents. Each component and its function will be explained below.

[1682] Children's devices

[1683] The device for children is equipped with an AI character that periodically converses with the child to identify their mental health and stressors. The content of the conversation is converted into text data using voice recognition technology and sent to a server.

[1684] server

[1685] The server uses a generative AI model to identify the child's stressors, using prompts such as the following to input the AI ​​model:

[1686] 1. Identifying stressors:

[1687] Identify stressors if your child is struggling with: Having trouble with friendships at school.

[1688] 2. Providing advice:

[1689] What advice should you offer parents if their child is struggling with friendships at school?

[1690] The server inputs these prompts into a generative AI model and uses the results to identify the child's stressors. It then generates specific advice for each identified stressor.

[1691] Parent's device

[1692] The parent's device will receive a notification sent from the server, which will include information about the child's stressors and specific advice on how to address them, allowing the parent to take appropriate measures to support their child's mental health.

[1693] Hardware and software used

[1694] Children's devices: smartphones, tablets, smart speakers, etc.

[1695] Server: Cloud server (e.g. AWS, Google Cloud)

[1696] Parent's device: smartphone, tablet, PC, etc.

[1697] Software: Python, OpenAI API, SMTP server (e.g. Gmail SMTP)

[1698] Specific examples

[1699] For example, if a child says to the device, "I'm having trouble with friends at school," the process will proceed as follows:

[1700] 1. The child's device converts the voice into text data and sends it to the server.

[1701] 2. The server uses a generative AI model to identify the stressor and uses the following prompt:

[1702] Identify stressors if your child is struggling with: Having trouble with friendships at school.

[1703] 3. The server generates advice for the identified stressors and uses the following prompt:

[1704] What advice should you offer parents if their child is struggling with friendships at school?

[1705] 4. The server notifies the parent device of the results obtained.

[1706] In this way, it becomes possible to quickly and accurately identify stressors in children and provide appropriate advice to parents.

[1707] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1708] Step 1:

[1709] A device for children begins a dialogue with the child. The device uses voice recognition technology to convert what the child says into text data. The input is the child's voice, and the output is text data. This text data serves as the basis for identifying the child's mental health status and stress factors.

[1710] Step 2:

[1711] The terminal sends the converted text data to the server. The input is text data, and the output is data sent to the server. The server receives this data and proceeds to the next processing step.

[1712] Step 3:

[1713] The server uses a generative AI model to identify children's stressors from text data. The input is the text data, and the output is the stressor identification results. The server inputs the AI ​​model using the following prompt sentence:

[1714] Identify stressors if your child is experiencing: [Text data]

[1715] The generative AI model identifies stressors based on this prompt.

[1716] Step 4:

[1717] The server generates specific advice for the identified stressors. The input is the stressor identification result, and the output is the specific advice. The server inputs the following prompt to the AI ​​model:

[1718] What advice should you offer parents if their child is struggling with [stressor]?

[1719] The generative AI model generates specific advice based on this prompt.

[1720] Step 5:

[1721] The server notifies the parent device of the generated advice and the results of identifying stress factors. The input is the advice and the results of identifying stress factors, and the output is the notification to the parent device. The server uses an SMTP server to send the notification to the parent's email address.

[1722] Step 6:

[1723] The parent's device receives the notification and the parent checks the content. The input is the notification from the server, and the output is the information the parent checks. Based on this information, the parent can take appropriate measures to support their child's mental health.

[1724] In this way, it becomes possible to quickly and accurately identify stressors in children and provide appropriate advice to parents.

[1725] Example 3

[1726] Next, a third embodiment of the third embodiment will be described. 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."

[1727] Previous stress check systems for children had the problem of being unable to accurately identify a child's emotional state and stress factors. Furthermore, they lacked the means to provide appropriate advice to parents, making it difficult to effectively manage their children's mental health.

[1728] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1729] In this invention, the server includes means for capturing the child's voice and video, means for converting the captured voice data into text, means for analyzing facial expressions from the video data, means for analyzing the text data and identifying the emotional state, and means for reporting the emotional state and its cause to the parent. This makes it possible to accurately identify the child's emotional state and stress factors and provide appropriate advice to the parent.

[1730] A "child-directed device" is an electronic device designed for use by children.

[1731] "Regular stress checks" are the process of assessing a child's stress levels at regular intervals.

[1732] An "artificial intelligence character" is a virtual character programmed to interact with children and analyze their emotions and stress levels.

[1733] "Children's mental health" refers to the state of a child's mental and emotional health.

[1734] "Stressors" refer to causes or situations that cause stress to children.

[1735] "Means of notifying parents of results and giving advice" refers to methods and functions for communicating analysis results to parents and proposing appropriate countermeasures.

[1736] "Means for capturing audio and video of children" refers to the ability to collect audio and video of children using a microphone and camera.

[1737] The "means for converting captured voice data into text" is a function that converts voice data into text data using voice recognition technology.

[1738] "Means for analyzing facial expressions from video data" refers to a function that uses video analysis technology to recognize a child's facial expressions and identify their emotional state.

[1739] The "means for analyzing text data and identifying an emotional state" is a function that uses natural language processing technology to analyze text data and determine a child's emotional state.

[1740] "Means for reporting emotional state and its causes to parents" refers to methods or functions for conveying the analysis results to parents and explaining the child's emotional state and its causes.

[1741] This invention is a system that uses an AI character installed on a device for children to identify a child's mental health condition and stress factors and notify the parents of the results. A specific embodiment of this system is described below.

[1742] First, the user (parent) prepares a device for the child to use. This device is equipped with a microphone and camera, and can capture the child's voice and video. The device captures the child's speech and facial expressions in real time and sends this data to the server.

[1743] The server converts the received audio data into text using Google Cloud Speech-to-Text. This process captures the child's speech as text data. The server then analyzes the child's facial expressions from the video data using the Microsoft Azure Face API. This identifies the child's emotional state.

[1744] Additionally, the server uses OpenAI's GPT-3 to analyze the text data and IBM Watson Tone Analyzer to identify the emotional state, making it clear what emotions the child is feeling. For example, if a child says, "I had a fight with my friend at school today," and shows an angry expression, the server will identify that the child is feeling angry.

[1745] Finally, the server reports the analysis results to the user (parent). For example, it may notify the parent that "your child is feeling angry because of a fight at school." This notification may also include appropriate advice. For example, it may provide specific advice such as "It is important to talk with your child and understand the cause of the fight."

[1746] As a concrete example, the following prompt sentence can be used:

[1747] Prompt: "Analyze audio and video recordings of a child talking about an incident at school and identify their emotional state. In particular, if they express anger or sadness, identify the cause of this."

[1748] In this way, the present invention can accurately identify the emotional state and stress factors of a child and provide appropriate advice to the parents. The flow of the identification process in the third embodiment will be described with reference to FIG.

[1749] Step 1:

[1750] The device captures audio and video of the child.

[1751] Specifically, the device uses a microphone and camera to record the child's voice and facial expressions in real time.

[1752] Input: Child's audio and video

[1753] Output: Captured audio and video data

[1754] Step 2:

[1755] The device sends the captured data to the server.

[1756] Specifically, the device transmits the captured audio and video data to the server using a secure communication protocol (e.g., HTTPS).

[1757] Input: Captured audio and video data

[1758] Output: Audio and video data sent to the server

[1759] Step 3:

[1760] The server converts the audio data into text.

[1761] Specifically, the server uses Google Cloud Speech-to-Text to convert the received voice data into text data.

[1762] Input: Audio data

[1763] Output: Text data

[1764] Step 4:

[1765] The server analyzes facial expressions from the video data.

[1766] Specifically, the server uses the Microsoft Azure Face API to analyze the child's facial expressions from the received video data and identify their emotional state.

[1767] Input: Video data

[1768] Output: Analyzed facial expression data

[1769] Step 5:

[1770] The server analyzes the text data to identify the emotional state.

[1771] Specifically, the server uses OpenAI's GPT-3 to analyze text data and IBM Watson Tone Analyzer to identify emotional states.

[1772] Input: Text data

[1773] Output: Identified emotional state

[1774] Step 6:

[1775] The server reports the emotional state and its cause to the user.

[1776] Specifically, the server notifies the user (parent) of the analysis results, explains the child's emotional state and its causes, and provides appropriate advice.

[1777] Input: Identified emotional state and its cause

[1778] Output: Analysis results and advice reported to the user

[1779] (Application example 3)

[1780] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[1781] Today's children are often exposed to stress and emotional fluctuations at home and school, which can result in poor mental health. However, it is difficult for parents and guardians to understand their children's emotional state and stressors in real time. Furthermore, if children are unable to express their emotions appropriately, problems may go unnoticed. This can delay appropriate measures to protect children's mental health.

[1782] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1783] In this invention, the server is installed in a device for children and includes an artificial intelligence character that performs regular stress checks, means for identifying the child's mental health condition and stress factors through conversation with the child, means for notifying the parents of the results and providing advice, means for analyzing the child's voice data and analyzing the emotional state, means for analyzing the child's video data and analyzing the emotional state from facial expressions, means for integrating the results of the emotion analysis of the voice data and video data and detecting abnormalities, and means for notifying the parents or guardians when an abnormality is detected. This makes it possible to grasp the child's emotional state and stress factors in real time, detect abnormalities early, and take appropriate action.

[1784] A "child-directed device" is an electronic device designed for use by children.

[1785] "Regular stress checks" are the process of assessing a child's stress levels at regular intervals.

[1786] An "artificial intelligence character" is a virtual character that uses AI technology to interact with children and analyze their emotions and stress.

[1787] "Conversation with a child" refers to the act of a child communicating with an AI character through voice or text.

[1788] "Mental health" refers to a child's mental and emotional stability and well-being.

[1789] "Stressors" refer to causes or situations that cause stress to children.

[1790] "Parent notification" refers to the act of informing parents or guardians of the results of the assessment of their child's emotional state and stress level.

[1791] "Advice tools" are ways of suggesting appropriate responses or actions to children and parents.

[1792] "Analyzing audio data" is the process of analyzing the content and tone of a child's speech to identify their emotional state.

[1793] "Means for analyzing emotional states" are techniques and methods for assessing a child's emotions from their voice and facial expressions.

[1794] "Analyzing video data" is the process of analyzing a child's facial expressions and movements to identify their emotional state.

[1795] "Means for analyzing emotional states from facial expressions" refers to techniques and methods that use video data to analyze children's facial expressions and evaluate their emotions.

[1796] "Sentiment analysis integration" refers to the process of combining the analysis results of audio data and video data to assess the overall emotional state.

[1797] "Anomaly detection methods" are techniques or methods for identifying unusual emotional states or stress levels.

[1798] "Means for notifying parents or guardians" refers to the method by which information about an abnormality is notified to parents or guardians when it is detected.

[1799] The system for implementing this invention is installed in a device for children. The device includes an AI character that performs regular stress checks and identifies mental health conditions and stress factors through conversations with the child. It also has a function to notify parents of the results and provide advice.

[1800] Hardware and software used

[1801] Hardware: smartphone, tablet, camera, microphone

[1802] Software: Python, OpenCV, TensorFlow, Transformers (Hugging Face emotion analysis model), DeepFace

[1803] Data processing and calculation

[1804] 1. Voice data analysis: The device's microphone is used to collect the child's voice, and a speech recognition model (Transformers) is used to analyze the child's emotional state. The voice data is converted into text and sentiment analysis is performed.

[1805] 2. Video Data Analysis: We collect video data of children using the device camera and analyze their emotional state from facial expressions using OpenCV and DeepFace. The video data is analyzed frame by frame, and emotions are identified from facial expressions.

[1806] 3. Sentiment Analysis Integration: The sentiment analysis results of audio and video data are integrated to evaluate the overall emotional state. If an anomaly is detected, a notification will be sent to parents or guardians.

[1807] Specific examples

[1808] For example, if a child says "I'm scared," and the speech recognition model detects "fear" and the facial expression recognition model also detects "fear," the system will detect an anomaly and send a notification to the parent, including the cause of the child's fear and advice on what the parent should do.

[1809] Prompt Sentence Examples

[1810] Please enter your child's voice data.

[1811] "Please enter your child's video data."

[1812] In this way, it is possible to grasp a child's emotional state and stress factors in real time, detect abnormalities early, and take appropriate action.

[1813] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1814] Step 1:

[1815] The device collects the child's voice data through a microphone. The input is the child's voice, and the output is a voice data file. This voice data is saved for subsequent voice recognition processing.

[1816] Step 2:

[1817] The device inputs the collected voice data into a voice recognition model (Transformers) and converts it into text data. The input is a voice data file, and the output is text data. This text data is used for sentiment analysis.

[1818] Step 3:

[1819] The device inputs the converted text data into a sentiment analysis model to identify the emotional state. The input is the text data, and the output is the emotional state (e.g., joy, sadness, fear, etc.). This emotional state is used in subsequent processing.

[1820] Step 4:

[1821] The device collects video data of the child through a camera. The input is the child's video, and the output is a video data file. This video data is saved for subsequent facial expression recognition processing.

[1822] Step 5:

[1823] The device inputs the collected video data into a facial expression recognition model (OpenCV and DeepFace) to identify the emotional state from the facial expressions. The input is a video data file, and the output is the emotional state (e.g., joy, sadness, fear, etc.). This emotional state is used in subsequent processing.

[1824] Step 6:

[1825] The terminal integrates the emotion analysis results of the audio data and the video data to evaluate the overall emotional state. The input is the emotional state of the audio data and the emotional state of the video data, and the output is the integrated emotional state. This integrated emotional state is used for anomaly detection.

[1826] Step 7:

[1827] The device detects anomalies based on the integrated emotional state. The input is the integrated emotional state, and the output is the anomaly detection result. If an anomaly is detected, a notification is sent to the parent or guardian.

[1828] Step 8:

[1829] The device sends a notification to parents or guardians when an abnormality is detected. The input is the anomaly detection result, and the output is a notification message. This notification message includes the child's emotional state, stress factors, and advice on what the parent should do.

[1830] 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.

[1831] "Example 1"

[1832] One embodiment of the present invention is a system that includes an emotion engine in which an AI character recognizes a child's emotions. This emotion engine analyzes the child's emotional state based on the child's words, facial expressions, tone of voice, and so on. For example, if a child says, "Today was fun," the emotion engine determines from that statement that the child is feeling joy. Similarly, if a child cries and says, "I can't take it anymore," the emotion engine determines from that statement and the crying that the child is feeling sadness or anger.

[1833] "Example 2"

[1834] Furthermore, the emotion engine adjusts the AI ​​character's response according to the child's emotional state. For example, if the AI ​​character determines that the child is feeling happy, it will offer pleasant conversations to the child. On the other hand, if the AI ​​character determines that the child is feeling sad or angry, it will respond empathetically to the child. This allows the AI ​​character to engage in dialogue that is adapted to the child's emotional state.

[1835] "Example 3"

[1836] The emotion engine also notifies parents of their child's emotional state. For example, if the emotion engine determines that a child is feeling sad or angry, it notifies the parent of that information. This allows parents to understand their child's emotional state and take appropriate action.

[1837] The processing flow of each embodiment will be described below.

[1838] "Example 1"

[1839] Step 1: The AI ​​character initiates a dialogue with the child.

[1840] Step 2: The emotion engine analyzes the child's emotional state based on their words, facial expressions, tone of voice, etc.

[1841] Step 3: The emotion engine communicates the analysis results to the AI ​​character.

[1842] "Example 2"

[1843] Step 1: The emotion engine determines the child's emotional state.

[1844] Step 2: The emotion engine issues instructions to adjust the AI ​​character's response based on the judgment results.

[1845] Step 3: The AI ​​character adjusts its dialogue to the child according to the instructions.

[1846] "Example 3"

[1847] Step 1: The emotion engine determines the child's emotional state.

[1848] Step 2: The emotion engine notifies the parent about the child's emotional state.

[1849] Step 3: Parents receive notifications and are aware of their child's emotional state.

[1850] Example 1

[1851] Next, a description will be given of Example 1 of Form 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."

[1852] Today's children often experience stress in various environments, such as at school and at home. However, it is difficult for children themselves to recognize this stress and deal with it appropriately. It is also difficult for parents and educators to accurately understand a child's stress level and take appropriate measures. Therefore, there is a need for a system that regularly checks children's mental health, identifies the causes of stress, and provides appropriate advice.

[1853] 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.

[1854] In this invention, the server is installed in a device for children and includes an artificial intelligence character that performs regular stress checks, means for identifying the child's mental health condition and stress factors through conversation with the child, means for notifying the parents of the results and providing advice, means for collecting data such as the child's comments, facial expressions, and tone of voice, means including an emotion engine for analyzing the collected data, and means for identifying the child's stress factors based on the analysis results. This makes it possible to accurately grasp the child's mental health condition and take appropriate measures.

[1855] A "child-directed device" is an electronic device designed for use by children.

[1856] "Regular stress checks" are the process of assessing a child's stress level at regular intervals.

[1857] An "artificial intelligence character" is a virtual character that interacts with children using artificial intelligence technology.

[1858] "Children's mental health" refers to the state of a child's mental and emotional health.

[1859] "Stressors" refer to the causes and situations that cause children to feel stressed.

[1860] "Means of notifying parents of results and giving advice" refers to the function of informing parents of the results of their child's stress state and suggesting appropriate ways to respond.

[1861] "Means for collecting data such as a child's statements, facial expressions, and tone of voice" refers to functions for obtaining information such as a child's words, facial expressions, and tone of voice.

[1862] An "emotion engine" is software or algorithms that analyze collected data and determine a child's emotional state.

[1863] "Means for identifying children's stress factors based on analysis results" refers to a function that uses the analysis results of the emotion engine to identify the specific causes of stress in children.

[1864] MODE FOR CARRYING OUT THE INVENTION

[1865] This invention is a system that uses an AI character installed on a device for children to check a child's mental health and identify the causes of stress. A specific embodiment of this system will be described below.

[1866] System configuration

[1867] The system consists of the following major components:

[1868] 1. Child-directed devices: Electronic devices designed for use by children, including hardware such as microphones, cameras, and speakers.

[1869] 2. Artificial Intelligence Character: A virtual character that interacts with children and uses natural language processing (NLP) technology to conduct conversations.

[1870] 3. Emotion engine: Software that analyzes data such as a child's speech, facial expressions, and tone of voice to determine their emotional state. Specifically, it uses Google Cloud Natural Language API and IBM Watson Tone Analyzer.

[1871] 4. Server: A central processing unit for analyzing the collected data and feeding back the results.

[1872] System Operation

[1873] The device initiates a conversation when the child speaks to the AI ​​character. For example, if the child says "Hello," the AI ​​character responds with "Hello, how was your day?" During this conversation, the device collects data such as the child's remarks, facial expressions, and tone of voice.

[1874] The collected data is sent from the device to a server. The server uses an emotion engine to analyze the data and determine the child's emotional state. For example, if a child says, "Today was fun," the emotion engine will determine from that statement that the child is feeling joy. If a child cries and says, "I can't take it anymore," the emotion engine will determine from that statement and the crying that the child is feeling sadness or anger.

[1875] The analysis results are fed back from the server to the device. The device then provides the feedback to the child through an AI character. For example, if the analysis result is "joy," the AI ​​character will respond, "You had fun today. What did you do?" If the analysis result is "sadness" or "anger," the AI ​​character will respond, "What's wrong? Did something happen?"

[1876] Furthermore, the server will identify the child's stressors based on the analysis results. For example, if a child avoids talking about school, it will determine that the child is experiencing school-related stress. This information will be notified to the parents, and appropriate advice will be provided.

[1877] Examples and prompts

[1878] Below are some specific examples and examples of prompts to input to the generative AI model.

[1879] Example 1: When a child says, "Today was fun," the device collects the statement and sends it to the server. The server's emotion engine analyzes it and determines that the child is feeling happy. The device responds through an AI character, "Today was fun, what did you do?"

[1880] Example 2: If a child cries and says, "I can't take it anymore," the device will collect the words and the crying and send them to the server. The server's emotion engine will analyze the data and determine that the child is feeling sad or angry. The device will respond through an AI character, asking, "What's wrong? Did something happen?"

[1881] Example prompt sentence:

[1882] "What stressors might be causing your child to avoid talking about school?"

[1883] "If a child says, 'I had fun today,' how does the emotion engine parse that?"

[1884] In this way, users can understand the operation of the system and utilize it appropriately.

[1885] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1886] Step 1:

[1887] The device starts a conversation by having the child speak to the AI ​​character. The user (child) might say, for example, "Hello." Based on this input, the device collects voice data, and the AI ​​character responds with, "Hello, how was your day?" In this step, voice data collection and an initial response are performed.

[1888] Step 2:

[1889] The device collects data such as the child's remarks, facial expressions, and tone of voice. Specifically, it records audio with a microphone and captures facial expressions with a camera. For example, if a child says, "Today was fun," the audio data and facial expression data are collected. In this step, audio data and video data are collected.

[1890] Step 3:

[1891] The device sends the collected data to the server. The data is encrypted and sent securely. For example, voice data and facial expression data are sent to the server. In this step, data is sent and encrypted.

[1892] Step 4:

[1893] The server analyzes the received data and uses an emotion engine to analyze the child's emotional state. Specifically, it uses software such as Google Cloud Natural Language API and IBM Watson Tone Analyzer. For example, it analyzes the voice data to determine whether the child is feeling "fun." In this step, data analysis and emotional state determination are performed.

[1894] Step 5:

[1895] The server feeds back the analysis results to the device. The device then provides feedback to the child through the AI ​​character. For example, if the analysis result is "joy," the AI ​​character responds, "You had fun today. What did you do?" In this step, the analysis results are fed back and a response is generated.

[1896] Step 6:

[1897] The server identifies the child's stressors based on the analysis results. For example, if a child avoids talking about school, it is determined that the child is experiencing stress related to school. This information is then notified to the parent, who can provide appropriate advice. In this step, the stressors are identified and notified to the parent.

[1898] (Application example 1)

[1899] Next, a description will be given of Application Example 1 of Form 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."

[1900] In modern society, it is important to identify children's mental health conditions and stressors early and respond appropriately. However, it is difficult for parents and educators to accurately grasp children's emotional states and stressors, and these are often overlooked. Furthermore, children themselves are often unable to express their emotions and stress appropriately. This puts children at risk of developing poor mental health.

[1901] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server is installed in a device for children and includes an AI character that performs regular stress checks, means for identifying a child's mental health condition and stress factors through conversation with the child, means for notifying the parents of the results and providing advice, means including an emotion engine that recognizes the child's emotional state by analyzing the child's words, facial expressions, and tone of voice, and means for storing the child's emotional state and stress factors in a database and performing long-term analysis. This makes it possible to identify a child's mental health condition and stress factors early and take appropriate measures.

[1902] A "child-oriented device" is an electronic device designed for everyday use by children.

[1903] "Regular stress checks" are the process of assessing a child's stress level at regular intervals.

[1904] An "AI character" is a virtual character equipped with artificial intelligence that collects and analyzes information by interacting with children.

[1905] "Conversation with a child" refers to the act of a child communicating with an AI character through voice or text.

[1906] "Mental health" refers to a child's mental stability and sense of well-being.

[1907] A "stressor" is a cause or situation that causes stress to a child.

[1908] "Means of notifying parents of results and giving advice" refers to a function that informs parents of their child's mental health status and stress factors and suggests appropriate responses.

[1909] The "Emotion Engine" is an artificial intelligence technology that analyzes a child's words, facial expressions, and tone of voice to recognize their emotional state.

[1910] A "database" is a system for storing and managing information about a child's emotional state and stressors.

[1911] "Longitudinal analysis" is the process of using collected data to assess changes in children's mental health and stressors over time.

[1912] ...

Claims

1. An AI character that is installed on the user's device and performs regular stress checks, A means for identifying the mental health condition and stress factors of the user through conversation with the user; A means for notifying the user's parents of the results and providing advice to them; A means for collecting data including the user's utterances, facial expressions, and tone of voice; means for analyzing said collected data, said means including an emotion engine; A means for identifying a cause of stress of the user based on an analysis result of the emotion engine; A system including:

2. 10. The system of claim 1, further comprising means for the AI ​​character to analyze an emotional state of the user.

3. 3. The system according to claim 1, further comprising means for the AI ​​character to identify a cause of stress for the user and provide advice corresponding to the cause.

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