System

Abstract

An object of a system according to an embodiment is to enable a parent to easily grasp the contents of daily statements and conversations of a child.SOLUTION: A system according to an embodiment includes devices, a generation AI, and a notifier. The device is worn by a child. The generation AI analyzes the statements and conversations collected by the devices worn by the child and generates a summary. The notifier notifies the parent's smartphone of the summary generated by the generation AI.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] Conventional technology makes it difficult for parents to understand the content of their children's daily comments and conversations, and there is room for improvement in terms of improving the quality of communication.

[0005] The system according to the embodiment aims to enable parents to easily understand the contents of their children's daily utterances and conversations. [Means for solving the problem]

[0006] The system according to the embodiment includes a device, a generation AI, and a notification unit. The device is worn by a child. The generation AI analyzes utterance and conversation data collected by the device worn by the child and generates a summary. The notification unit notifies the parent's smartphone of the summary generated by the generation AI. [Effects of the Invention]

[0007] The system according to the embodiment can enable parents to easily understand the contents of their children's daily utterances and conversations. [Brief explanation of the drawings]

[0008] [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. DETAILED DESCRIPTION OF THE INVENTION

[0009] 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.

[0010] First, the terms used in the following description will be explained.

[0011] 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).

[0012] 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.

[0013] 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.

[0014] 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), and Bluetooth (registered trademark).

[0015] 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."

[0016] [First embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] 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.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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).

[0019] 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.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. 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 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. 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.

[0022] 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.

[0023] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] 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.

[0025] 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. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0027] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device owned by a user (e.g., a mobile phone, a robot, a home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) The system according to the embodiment of the present invention uses a device worn by a child to generate a summary of the day's utterances and conversations using a generation AI and notify the parent's smartphone. By summarizing the child's utterances and conversations and notifying the parent, the parent can keep track of how their child is doing throughout the day.

[0029] A system according to an embodiment includes a device worn by a child, a generation AI, and a parent's smartphone. The device worn by the child collects the child's speech and conversation. For example, the device analyzes the child's speech and conversation in real time and extracts important information. The device is designed to be lightweight and portable, allowing the child to use it comfortably in their daily lives. The generation AI analyzes the data of the child's speech and conversation and generates a summary. For example, the generation AI summarizes the content of the speech and conversation using a text generation AI (e.g., LLM). The generation AI can also summarize the content of the speech and conversation using a multimodal generation AI. The generation AI can also extract important points and generate a summary. The parent's smartphone notifies the parent of the summary generated by the generation AI. For example, the parent's smartphone can receive the summary via a push notification. The parent's smartphone can also receive the summary via email notification. The parent's smartphone can also check the summary through a dedicated app. In this way, the system summarizes the child's speech and conversation and notifies the parent, allowing the parent to keep track of how their child is doing throughout the day.

[0030] The device worn by the child can be a wristwatch type or a pendant type. For example, the device worn by the child can be a wristwatch type and worn on the child's wrist. Alternatively, the device worn by the child can be a pendant type and worn around the child's neck. Alternatively, the device worn by the child can be incorporated into clothing, for example, so that the child can wear it naturally. This allows the child to wear the device without feeling uncomfortable.

[0031] The device worn by the child is equipped with a biosensor and can monitor the child's health condition. The device worn by the child may, for example, be equipped with a heart rate sensor and monitor the child's heart rate in real time. For example, it may record fluctuations in heart rate during exercise and rest, and notify parents if any abnormalities are detected. The device worn by the child may, for example, be equipped with a body temperature sensor and constantly monitor the child's body temperature. For example, it may send an alert to parents if signs of fever are detected. The device worn by the child may, for example, be equipped with an oxygen saturation sensor and measure the child's blood oxygen level. For example, it may notify parents if a hypoxic state is detected. This allows the child's health condition to be understood in real time.

[0032] The device worn by the child is equipped with a GPS function and can notify parents of the child's location information in real time. The device worn by the child, for example, has a built-in GPS chip and tracks the child's location information in real time. For example, parents can check the route their child takes home from school. The device worn by the child also installs a dedicated app on the parent's smartphone, for example, which displays the child's current location on a map. For example, this allows the child's location to be quickly identified if they get lost. The device worn by the child also has, for example, a geofencing function that notifies parents when the child enters or leaves a specific area. For example, an alert is sent if the child leaves school grounds. This allows the child's location to be known in real time.

[0033] The device worn by the child can be incorporated into clothing. The device worn by the child can be built into, for example, a pocket of a shirt or jacket, allowing the child to wear it naturally. For example, the device can be stored in a removable pocket. The device worn by the child can also be built into, for example, a shoe insole, allowing the child to wear the device simply by putting on the shoe. For example, a sensor or battery can be built into the shoe insole. The device worn by the child can also be built into, for example, a hat or headband, allowing the device to function simply by the child wearing it on their head. For example, a sensor or communication module can be placed inside the hat. This allows the child to wear the device naturally.

[0034] The device worn by each child can be worn by multiple children and can analyze group conversations and activities. The device worn by each child can, for example, be worn by multiple children and analyze the content of group conversations. For example, it can extract keywords that appear frequently in the conversations and notify parents. The device worn by each child can also, for example, communicate with each other and collect group activity data. For example, it can record the time and place when children are playing together. The device worn by each child can also, for example, analyze the emotional state of the group and notify parents. For example, it can estimate whether the entire group is having fun or feeling stressed. This makes it possible to analyze group conversations and activities.

[0035] The generation AI can automatically classify a child's interests and hobbies based on the summary content and make suggestions to parents. For example, the generation AI analyzes the summary content and automatically classifies a child's interests and hobbies. For example, it extracts themes that children frequently talk about and makes suggestions to parents. The generation AI can also build a system that classifies a child's interests and hobbies based on the summary content and makes suggestions to parents. For example, it can extract a child's favorite activities and hobbies from the summary. The generation AI can also analyze the content of a child's comments and automatically classify their interests and hobbies to make appropriate suggestions to parents. For example, it can suggest books and movies that the child is interested in. This makes it easier for parents to support their children's development by automatically classifying a child's interests and making suggestions to parents.

[0036] The generation AI can automatically translate the summary content into different languages, achieving multilingual support. The generation AI, for example, automatically translates the summary content into different languages, achieving multilingual support. For example, it provides a summary translated into English or Spanish to a parent. The generation AI can also, for example, build a system that automatically translates the summary content into different languages, allowing a parent to check the summary in multiple languages. For example, it can display the summary in the language selected by the parent. The generation AI can also, for example, develop a multilingual summary system that provides summaries in different languages ​​in real time. For example, it can handle cases where the language spoken by the child and the language spoken by the parent are different. This allows multilingual support by automatically translating the summary content into different languages.

[0037] The generation AI can visualize the summary content to allow parents to intuitively understand it. For example, the generation AI can visualize the summary content to allow parents to intuitively understand it. For example, the summary can be displayed using graphs or charts. The generation AI can also build a system that visualizes the summary content to allow parents to visually grasp the information. For example, the child's activities can be displayed using icons or illustrations. The generation AI can also provide a visualized summary to allow parents to intuitively understand how their child's day went. For example, the child's emotional state can be displayed using different colors. In this way, visualizing the summary content makes it easier for parents to intuitively understand.

[0038] The content of notifications sent to parents' smartphones can be customized, allowing parents to receive only the information that interests them. For example, a function that allows parents to customize the content of notifications sent to parents' smartphones can be provided, allowing them to receive only the information that interests them. For example, a setting can be made to notify only information related to their child's academic performance. Furthermore, a system for customizing the content of notifications can be built, allowing parents to prioritize notification of information that interests them. For example, information related to their child's friendships can be selected. Furthermore, a function that allows parents to filter the content of notifications sent to parents' smartphones can be provided, allowing them to eliminate unnecessary information. For example, notifications can be customized based on specific keywords. This allows parents to receive only the information that interests them, improving the ease of information reception.

[0039] A function will be added that allows parents to send feedback on the content of notifications, and the generation AI will be able to learn from that feedback. A function will be provided that allows parents to send feedback on the content of notifications, and the generation AI will be able to learn from that feedback. For example, by evaluating whether the notification was useful. A function will also be added that allows parents to send their opinions and thoughts on the content of notifications. For example, by suggesting ways to improve the content of notifications. A system will also be built in which the generation AI will learn from parental feedback and optimize the content of notifications. For example, it will prioritize notifications of information that parents prefer. This will allow the content of notifications to be optimized by learning from parental feedback.

[0040] A function will be added to read out the contents of notifications sent to parents' smartphones, allowing them to receive information even in situations where they cannot visually check the contents. A function will be added to read out the contents of notifications sent to parents' smartphones, allowing them to receive information even in situations where they cannot visually check the contents. For example, notifications can be received by voice while driving or cooking. A voice read-out function will also be provided, allowing parents to check the contents of notifications without operating their smartphones. For example, notifications can be read out through a voice assistant. A system will also be built that allows parents to check the contents of notifications by voice, allowing them to receive information even in situations where visual confirmation is difficult. For example, the contents of notifications can be automatically converted into voice. This will improve convenience by allowing parents to receive information even in situations where they cannot visually check the contents.

[0041] By allowing the contents of notifications sent to parents' smartphones to be shared with the entire family, the entire family can understand the status of their children. By providing a function that allows the contents of notifications sent to parents' smartphones to be shared with the entire family, the entire family can understand the status of their children. For example, all family members can use the same app to receive notifications. In addition, a system can be created where all family members can check the contents of notifications and share the status of their children. For example, notification contents can be sent to a family group chat. In addition, by sharing the contents of notifications with the entire family, the entire family can keep an eye on the growth and changes of their children. For example, all family members can keep an eye on how their children are doing throughout the day. This allows all family members to keep an eye on their children's growth, making it possible for the entire family to keep an eye on their children's growth.

[0042] Data collected by devices can be encrypted to prevent unauthorized access by third parties. A system can be built to encrypt data collected by devices and prevent unauthorized access by third parties. For example, AES encryption technology can be used to protect data. Privacy can also be protected by encrypting data collected by devices. For example, encryption protocols can be used when data is transmitted. Data collected by devices can also be encrypted and sent to the parent's smartphone. For example, SSL / TLS encryption can be used when data is transferred. This encryption of data can prevent unauthorized access by third parties.

[0043] A function can be added to automatically delete data collected by devices after a certain period of time. Privacy can be protected by adding a function to automatically delete data collected by devices after a certain period of time. For example, data can be automatically deleted after 30 days. Privacy can also be protected by building a system to automatically delete data collected by devices. For example, data can be deleted after a period set by parents. Privacy can also be protected by automatically deleting data collected by devices after a certain period of time. For example, parents can set the period for which data is stored. This allows privacy to be protected by automatically deleting data after a certain period of time.

[0044] It is possible to provide a dashboard that allows parents to monitor device usage in real time. A system is constructed that provides a dashboard that allows parents to monitor device usage in real time. For example, parents can check the device status on a smartphone. Privacy is also protected by providing a dashboard that allows parents to monitor device usage in real time. For example, the device's operating status and data collection status are displayed. Privacy is also protected by providing a dashboard that allows parents to monitor device usage in real time. For example, parents can change device settings remotely. This allows parents to monitor device usage in real time, thereby protecting privacy.

[0045] Parents can customize the privacy policy regarding device use. Provide a function that allows parents to customize the privacy policy regarding device use. For example, parents can set the scope of data collection and storage period. Also, build a system that allows parents to customize the privacy policy regarding device use. For example, parents can set the scope of data sharing and access permissions. Also, privacy can be protected by allowing parents to customize the privacy policy regarding device use. For example, parents can set the purpose of data use. This allows parents to customize the privacy policy, thereby protecting privacy.

[0046] When a parent types a question, the generation AI can automatically suggest related additional information. We are building a system in which the generation AI automatically suggests related additional information when a parent types a question. For example, if a parent types, "Tell me about what happened at school today," the generation AI would suggest things like, "What you played with friends about" or "What the class was about." The generation AI also suggests related additional information to a parent's question, making it easier for parents to obtain detailed information. For example, if a parent types, "Tell me about today's homework," the generation AI would suggest things like, "What the homework was about" and "Due date for submission." The generation AI also suggests related additional information when a parent types a question, making it easier for parents to obtain detailed information. For example, if a parent types, "Tell me about today's school lunch," the generation AI would suggest things like, "The menu" and "My child's impressions." This makes it easier for parents to obtain detailed information by suggesting related additional information when they type a question.

[0047] Answers to questions can be provided by comparing them with past data, making it possible to show a child's growth and changes. We are building a system that provides answers to parents' questions by comparing them with past data. For example, when a parent asks, "Tell me about my grades today," the generating AI will provide an answer by comparing them with past grades. In addition, by comparing the answers to questions with past data, it is possible to show a child's growth and changes. For example, when a parent asks, "Tell me about the results of today's sports day," the generating AI will provide an answer by comparing them with past sports day results. In addition, by providing answers to parents' questions by comparing them with past data, it becomes easier to understand a child's growth and changes. For example, when a parent asks, "Tell me about how your drawing turned out today," the generating AI will provide an answer by comparing it with past drawings. In this way, by comparing answers to questions with past data, it becomes easier to understand a child's growth and changes.

[0048] Convenience can be improved by adding a function that allows parents to input questions by voice. A system that improves convenience can be built by adding a function that allows parents to input questions by voice. For example, when a parent speaks a question into their smartphone, the generation AI analyzes the question and provides an answer. A voice input function is also provided, allowing parents to input questions by voice. For example, when a parent says, "Tell me about what happened at school today," the generation AI will respond to the question. Convenience can also be improved by adding a function that allows parents to input questions by voice. For example, it would allow parents to input questions by voice even when they are busy. This would improve convenience by allowing parents to input questions by voice.

[0049] Answers to questions can be provided in the form of visual notes or mind maps. A system can be built in which answers to questions are provided in visual note format, making it easier for parents to understand. For example, the answers can be shown in diagrams or illustrations. Answers to questions can also be provided in mind map format, making it easier for parents to organize information. For example, the answers can be visually displayed with related keywords or concepts. Answers can also be provided in the form of visual notes or mind maps, making it easier for parents to understand the answers intuitively. For example, the answers can be displayed in different colors. In this way, answers can be provided in the form of visual notes or mind maps, making it easier for parents to understand intuitively.

[0050] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0051] The device worn by the child is equipped with environmental sensors and can collect information about the surrounding environment. For example, the device may be equipped with a temperature sensor and can monitor the temperature of the environment in which the child is spending time. The device may also be equipped with a humidity sensor and can measure the humidity around the child. Furthermore, the device may be equipped with a noise sensor and can record the noise level in the child's location. This allows parents to understand the environment in which their child is spending time.

[0052] The device worn by the child is equipped with learning support functions and can monitor the child's learning status. For example, the device can record what the child is studying and track their learning progress. The device can also determine whether the child is concentrating while studying and notify parents of the level of concentration. Furthermore, the device can record any doubts or questions the child has while studying and notify parents. This allows parents to understand their child's learning status and provide appropriate support.

[0053] Devices worn by children are equipped with a function to monitor the amount of exercise, allowing parents to understand their children's exercise habits. For example, the device is equipped with a pedometer and can record the number of steps a child takes in a day. The device is also equipped with an acceleration sensor and can measure the amount of exercise a child performs. Furthermore, the device can use its GPS function to record the route a child takes when exercising. This allows parents to understand their children's exercise habits and use the information to help manage their health.

[0054] The device worn by the child is equipped with a sleep monitoring function to understand the child's sleep status. For example, the device can record the child's movements while sleeping and evaluate the quality of sleep. The device can also monitor the child's heart rate while sleeping using a heart rate sensor. Furthermore, the device is equipped with an audio sensor to record the child's snoring and talking in their sleep. This allows parents to understand their child's sleep status and take measures to improve it if necessary.

[0055] The processing flow of the first embodiment will be briefly explained below.

[0056] Step 1: The device worn by the child collects the child's speech and conversation. For example, the device analyzes the child's speech and conversation in real time and extracts important information. The device is also designed to be lightweight and easy to carry, so that children can use it comfortably in their daily lives. Step 2: The generation AI analyzes the data of the child's utterances and conversations and generates a summary. For example, the generation AI may use a text generation AI (e.g., LLM) to summarize the content of the utterances and conversations. The generation AI may also use a multimodal generation AI to summarize the content of the utterances and conversations. The generation AI may also extract key points and generate a summary. Step 3: The notification unit notifies the parent's smartphone of the summary generated by the generation AI. For example, the parent's smartphone can receive the summary via push notification. Alternatively, the parent's smartphone can receive the summary via email notification. Alternatively, the parent's smartphone can check the summary through a dedicated app.

[0057] (Example 2) The system according to the embodiment of the present invention uses a device worn by a child to generate a summary of the day's utterances and conversations using a generation AI and notify the parent's smartphone. By summarizing the child's utterances and conversations and notifying the parent, the parent can keep track of how their child is doing throughout the day.

[0058] A system according to an embodiment includes a device worn by a child, a generation AI, and a parent's smartphone. The device worn by the child collects the child's speech and conversation. For example, the device analyzes the child's speech and conversation in real time and extracts important information. The device is designed to be lightweight and portable, allowing the child to use it comfortably in their daily lives. The generation AI analyzes the data of the child's speech and conversation and generates a summary. For example, the generation AI summarizes the content of the speech and conversation using a text generation AI (e.g., LLM). The generation AI can also summarize the content of the speech and conversation using a multimodal generation AI. The generation AI can also extract important points and generate a summary. The parent's smartphone notifies the parent of the summary generated by the generation AI. For example, the parent's smartphone can receive the summary via a push notification. The parent's smartphone can also receive the summary via email notification. The parent's smartphone can also check the summary through a dedicated app. In this way, the system summarizes the child's speech and conversation and notifies the parent, allowing the parent to keep track of how their child is doing throughout the day.

[0059] The device worn by the child can be a wristwatch type or a pendant type. For example, the device worn by the child can be a wristwatch type and worn on the child's wrist. Alternatively, the device worn by the child can be a pendant type and worn around the child's neck. Alternatively, the device worn by the child can be incorporated into clothing, for example, so that the child can wear it naturally. This allows the child to wear the device without feeling uncomfortable.

[0060] The device worn by the child is equipped with a biosensor and can monitor the child's health condition. The device worn by the child may, for example, be equipped with a heart rate sensor and monitor the child's heart rate in real time. For example, it may record fluctuations in heart rate during exercise and rest, and notify parents if any abnormalities are detected. The device worn by the child may, for example, be equipped with a body temperature sensor and constantly monitor the child's body temperature. For example, it may send an alert to parents if signs of fever are detected. The device worn by the child may, for example, be equipped with an oxygen saturation sensor and measure the child's blood oxygen level. For example, it may notify parents if a hypoxic state is detected. This allows the child's health condition to be understood in real time.

[0061] The device worn by the child is equipped with a GPS function and can notify parents of the child's location information in real time. The device worn by the child, for example, has a built-in GPS chip and tracks the child's location information in real time. For example, parents can check the route their child takes home from school. The device worn by the child also installs a dedicated app on the parent's smartphone, for example, which displays the child's current location on a map. For example, this allows the child's location to be quickly identified if they get lost. The device worn by the child also has, for example, a geofencing function that notifies parents when the child enters or leaves a specific area. For example, an alert is sent if the child leaves school grounds. This allows the child's location to be known in real time.

[0062] The device worn by the child is equipped with an emotion estimation function and can analyze the child's emotional state in real time and notify the parent. The device worn by the child is, for example, equipped with a face recognition camera and analyzes the child's facial expressions to estimate the emotional state. For example, it detects smiling or crying faces and notifies the parent. The device worn by the child can also use voice analysis technology to estimate the emotion from the tone and tempo of the child's voice. For example, it can detect emotions such as anger or sadness and send an alert to the parent. The device worn by the child can also use biosensors to estimate the emotional state from heart rate and skin electrodermal response. For example, it can detect stress or excitement and notify the parent. This allows the child's emotional state to be understood in real time.

[0063] The device worn by the child can be incorporated into clothing. The device worn by the child can be built into, for example, a pocket of a shirt or jacket, allowing the child to wear it naturally. For example, the device can be stored in a removable pocket. The device worn by the child can also be built into, for example, a shoe insole, allowing the child to wear the device simply by putting on the shoe. For example, a sensor or battery can be built into the shoe insole. The device worn by the child can also be built into, for example, a hat or headband, allowing the device to function simply by the child wearing it on their head. For example, a sensor or communication module can be placed inside the hat. This allows the child to wear the device naturally.

[0064] The device worn by each child can be worn by multiple children and can analyze group conversations and activities. The device worn by each child can, for example, be worn by multiple children and analyze the content of group conversations. For example, it can extract keywords that appear frequently in the conversations and notify parents. The device worn by each child can also, for example, communicate with each other and collect group activity data. For example, it can record the time and place when children are playing together. The device worn by each child can also, for example, analyze the emotional state of the group and notify parents. For example, it can estimate whether the entire group is having fun or feeling stressed. This makes it possible to analyze group conversations and activities.

[0065] A device worn by a child can use an emotion estimation function to send an alert to a parent when the child feels a specific emotion. The device worn by a child, for example, analyzes the child's emotional state in real time and sends an alert to the parent when a specific emotion is detected. For example, it notifies the parent when the child feels strong anxiety. The device worn by a child can also use the emotion estimation function to send an alert to the parent when the child is in an excited state. For example, by notifying the parent when the child is excited, the parent can take appropriate action. The device worn by a child can also detect, for example, sadness or anger when the child feels that emotion and send an alert to the parent. For example, it notifies the parent when the child is crying. In this way, the parent can be notified when the child feels a specific emotion.

[0066] The generation AI can analyze the tone and tempo of a child's speech and conversation and reflect this in the summary. For example, the generation AI can analyze not only the content of a child's speech but also the tone and tempo and reflect this in the summary. For example, if a child is speaking excitedly, that tone will be included in the summary. The generation AI can also analyze the tone and tempo of a child's speech and notify the parent. For example, it can reflect in the summary whether the child is speaking calmly or hurriedly. The generation AI can also estimate a child's emotional state by analyzing the tone and tempo of speech and reflect this in the summary. For example, if a child is speaking happily, that emotion will be included in the summary. In this way, by analyzing the tone and tempo of a child's speech and reflecting this in the summary, parents can better understand their child's emotional state.

[0067] The generation AI can automatically classify a child's interests and hobbies based on the summary content and make suggestions to parents. For example, the generation AI analyzes the summary content and automatically classifies a child's interests and hobbies. For example, it extracts themes that children frequently talk about and makes suggestions to parents. The generation AI can also build a system that classifies a child's interests and hobbies based on the summary content and makes suggestions to parents. For example, it can extract a child's favorite activities and hobbies from the summary. The generation AI can also analyze the content of a child's comments and automatically classify their interests and hobbies to make appropriate suggestions to parents. For example, it can suggest books and movies that the child is interested in. This makes it easier for parents to support their children's development by automatically classifying a child's interests and making suggestions to parents.

[0068] The generation AI can use the emotion estimation function to analyze the emotional nuances of a child's speech and reflect them in the summary. For example, the generation AI analyzes the content of a child's speech and reflects the emotional nuances in the summary. For example, if a child sounds happy, that emotion is included in the summary. The generation AI can also use the emotion estimation function to build a system that analyzes the emotional nuances of a child's speech and reflects them in the summary. For example, if a child sounds sad, that emotion is included in the summary. The generation AI can also analyze the emotional nuances of a child's speech and reflect them in the summary, making it easier for parents to understand their child's emotional state. For example, if a child is angry, that emotion is included in the summary. In this way, by analyzing the emotional nuances of a child's speech and reflecting them in the summary, parents can better understand their child's emotional state.

[0069] The generation AI can automatically translate the summary content into different languages, achieving multilingual support. The generation AI, for example, automatically translates the summary content into different languages, achieving multilingual support. For example, it provides a summary translated into English or Spanish to a parent. The generation AI can also, for example, build a system that automatically translates the summary content into different languages, allowing a parent to check the summary in multiple languages. For example, it can display the summary in the language selected by the parent. The generation AI can also, for example, develop a multilingual summary system that provides summaries in different languages ​​in real time. For example, it can handle cases where the language spoken by the child and the language spoken by the parent are different. This allows multilingual support by automatically translating the summary content into different languages.

[0070] The generation AI can visualize the summary content to allow parents to intuitively understand it. For example, the generation AI can visualize the summary content to allow parents to intuitively understand it. For example, the summary can be displayed using graphs or charts. The generation AI can also build a system that visualizes the summary content to allow parents to visually grasp the information. For example, the child's activities can be displayed using icons or illustrations. The generation AI can also provide a visualized summary to allow parents to intuitively understand how their child's day went. For example, the child's emotional state can be displayed using different colors. In this way, visualizing the summary content makes it easier for parents to intuitively understand.

[0071] The generation AI can use the emotion estimation function to collect parents' emotional reactions to the summary content and improve the accuracy of the summary. For example, the generation AI collects parents' emotional reactions to the summary content and improves the accuracy of the summary based on that data. For example, it prioritizes the adoption of summaries to which parents have shown positive reactions. The generation AI can also use the emotion estimation function to analyze parents' emotional reactions to the summary content and build a system to improve the accuracy of the summary. For example, it can revise summaries to which parents have shown negative reactions. The generation AI can also build a feedback loop to improve the accuracy of the summary based on parents' emotional reaction data. For example, it can regenerate summaries based on parents' emotional scores. In this way, by collecting parents' emotional reactions and improving the accuracy of the summary, more appropriate information can be provided.

[0072] The content of notifications sent to parents' smartphones can be customized, allowing parents to receive only the information that interests them. For example, a function that allows parents to customize the content of notifications sent to parents' smartphones can be provided, allowing them to receive only the information that interests them. For example, a setting can be made to notify only information related to their child's academic performance. Furthermore, a system for customizing the content of notifications can be built, allowing parents to prioritize notification of information that interests them. For example, information related to their child's friendships can be selected. Furthermore, a function that allows parents to filter the content of notifications sent to parents' smartphones can be provided, allowing them to eliminate unnecessary information. For example, notifications can be customized based on specific keywords. This allows parents to receive only the information that interests them, improving the ease of information reception.

[0073] A function will be added that allows parents to send feedback on the content of notifications, and the generation AI will be able to learn from that feedback. A function will be provided that allows parents to send feedback on the content of notifications, and the generation AI will be able to learn from that feedback. For example, by evaluating whether the notification was useful. A function will also be added that allows parents to send their opinions and thoughts on the content of notifications. For example, by suggesting ways to improve the content of notifications. A system will also be built in which the generation AI will learn from parental feedback and optimize the content of notifications. For example, it will prioritize notifications of information that parents prefer. This will allow the content of notifications to be optimized by learning from parental feedback.

[0074] The emotion estimation function can be used to analyze parents' emotional reactions to notification content and optimize the content and timing of notifications. A system can be built using the emotion estimation function to analyze parents' emotional reactions to notification content and optimize the content and timing of notifications. For example, notifications can be sent during times when parents are showing positive emotions. The content of notifications can also be adjusted based on the parent's emotional reaction data. For example, if a parent is feeling stressed, only important information can be notified. The emotion estimation function can also be used to send notifications according to the parent's emotional state. For example, sending notifications during times when the parent is relaxed can improve the ease with which the information is received. In this way, by analyzing parents' emotional reactions and optimizing the content and timing of notifications, the ease with which the information is received can be improved.

[0075] A function will be added to read out the contents of notifications sent to parents' smartphones, allowing them to receive information even in situations where they cannot visually check the contents. A function will be added to read out the contents of notifications sent to parents' smartphones, allowing them to receive information even in situations where they cannot visually check the contents. For example, notifications can be received by voice while driving or cooking. A voice read-out function will also be provided, allowing parents to check the contents of notifications without operating their smartphones. For example, notifications can be read out through a voice assistant. A system will also be built that allows parents to check the contents of notifications by voice, allowing them to receive information even in situations where visual confirmation is difficult. For example, the contents of notifications can be automatically converted into voice. This will improve convenience by allowing parents to receive information even in situations where they cannot visually check the contents.

[0076] By allowing the contents of notifications sent to parents' smartphones to be shared with the entire family, the entire family can understand the status of their children. By providing a function that allows the contents of notifications sent to parents' smartphones to be shared with the entire family, the entire family can understand the status of their children. For example, all family members can use the same app to receive notifications. In addition, a system can be created where all family members can check the contents of notifications and share the status of their children. For example, notification contents can be sent to a family group chat. In addition, by sharing the contents of notifications with the entire family, the entire family can keep an eye on the growth and changes of their children. For example, all family members can keep an eye on how their children are doing throughout the day. This allows all family members to keep an eye on their children's growth, making it possible for the entire family to keep an eye on their children's growth.

[0077] Using the emotion estimation function, it is possible to monitor the parent's emotional reaction to the notification content in real time and change the notification content as necessary. Using the emotion estimation function, we will build a system that monitors the parent's emotional reaction to the notification content in real time and changes the notification content as necessary. For example, if the parent is feeling stressed, the notification content will be reduced. In addition, the notification content will be adjusted in real time based on the parent's emotional reaction data. For example, if the parent shows positive emotions, detailed information will be notified. In addition, the emotion estimation function will be used to provide notifications according to the parent's emotional state. For example, by sending notifications at times when the parent is relaxed, it will be easier for the parent to accept the information. In this way, by monitoring the parent's emotional reaction in real time and optimizing the notification content, it will be easier for the parent to accept the information.

[0078] Data collected by devices can be encrypted to prevent unauthorized access by third parties. A system can be built to encrypt data collected by devices and prevent unauthorized access by third parties. For example, AES encryption technology can be used to protect data. Privacy can also be protected by encrypting data collected by devices. For example, encryption protocols can be used when data is transmitted. Data collected by devices can also be encrypted and sent to the parent's smartphone. For example, SSL / TLS encryption can be used when data is transferred. This encryption of data can prevent unauthorized access by third parties.

[0079] A function can be added to automatically delete data collected by devices after a certain period of time. Privacy can be protected by adding a function to automatically delete data collected by devices after a certain period of time. For example, data can be automatically deleted after 30 days. Privacy can also be protected by building a system to automatically delete data collected by devices. For example, data can be deleted after a period set by parents. Privacy can also be protected by automatically deleting data collected by devices after a certain period of time. For example, parents can set the period for which data is stored. This allows privacy to be protected by automatically deleting data after a certain period of time.

[0080] The emotion estimation function can be used to suspend device functions when a child has a privacy concern. A system is constructed using the emotion estimation function to suspend device functions when a child has a privacy concern. For example, the device is suspended when a child feels anxious. The child's emotional state is analyzed, and the device functions are suspended when a privacy concern is detected. For example, the device is suspended when a child feels stressed. The emotion estimation function can also be used to protect privacy by suspending device functions when a child has a privacy concern. For example, the device is suspended when a child shows unpleasant emotions. In this way, privacy can be protected by suspending device functions when a child has a privacy concern.

[0081] It is possible to provide a dashboard that allows parents to monitor device usage in real time. A system is constructed that provides a dashboard that allows parents to monitor device usage in real time. For example, parents can check the device status on a smartphone. Privacy is also protected by providing a dashboard that allows parents to monitor device usage in real time. For example, the device's operating status and data collection status are displayed. Privacy is also protected by providing a dashboard that allows parents to monitor device usage in real time. For example, parents can change device settings remotely. This allows parents to monitor device usage in real time, thereby protecting privacy.

[0082] Parents can customize the privacy policy regarding device use. Provide a function that allows parents to customize the privacy policy regarding device use. For example, parents can set the scope of data collection and storage period. Also, build a system that allows parents to customize the privacy policy regarding device use. For example, parents can set the scope of data sharing and access permissions. Also, privacy can be protected by allowing parents to customize the privacy policy regarding device use. For example, parents can set the purpose of data use. This allows parents to customize the privacy policy, thereby protecting privacy.

[0083] The emotion estimation function can be used to send an alert to parents when a child has a privacy concern. A system is built that uses the emotion estimation function to send an alert to parents when a child has a privacy concern. For example, the system notifies parents when a child feels anxious. The system also analyzes a child's emotional state and sends an alert to parents when a privacy concern is detected. For example, the system notifies parents when a child feels stressed. The emotion estimation function can also be used to protect privacy by sending an alert to parents when a child has a privacy concern. For example, the system notifies parents when a child shows unpleasant emotions. This makes it possible to protect privacy by notifying parents when a child has a privacy concern.

[0084] When a parent types a question, the generation AI can automatically suggest related additional information. We are building a system in which the generation AI automatically suggests related additional information when a parent types a question. For example, if a parent types, "Tell me about what happened at school today," the generation AI would suggest things like, "What you played with friends about" or "What the class was about." The generation AI also suggests related additional information to a parent's question, making it easier for parents to obtain detailed information. For example, if a parent types, "Tell me about today's homework," the generation AI would suggest things like, "What the homework was about" and "Due date for submission." The generation AI also suggests related additional information when a parent types a question, making it easier for parents to obtain detailed information. For example, if a parent types, "Tell me about today's school lunch," the generation AI would suggest things like, "The menu" and "My child's impressions." This makes it easier for parents to obtain detailed information by suggesting related additional information when they type a question.

[0085] Answers to questions can be provided by comparing them with past data, making it possible to show a child's growth and changes. We are building a system that provides answers to parents' questions by comparing them with past data. For example, when a parent asks, "Tell me about my grades today," the generating AI will provide an answer by comparing them with past grades. In addition, by comparing the answers to questions with past data, it is possible to show a child's growth and changes. For example, when a parent asks, "Tell me about the results of today's sports day," the generating AI will provide an answer by comparing them with past sports day results. In addition, by providing answers to parents' questions by comparing them with past data, it becomes easier to understand a child's growth and changes. For example, when a parent asks, "Tell me about how your drawing turned out today," the generating AI will provide an answer by comparing it with past drawings. In this way, by comparing answers to questions with past data, it becomes easier to understand a child's growth and changes.

[0086] The emotion estimation function can be used to analyze a child's emotional response to a parent's question and reflect it in the answer. A system is constructed that uses the emotion estimation function to analyze a child's emotional response to a parent's question and reflects the results in the answer. For example, if a child shows positive emotion in response to a question, that emotion is included in the answer. In addition, by analyzing a child's emotional response to a parent's question and reflecting it in the answer, it becomes easier for parents to understand their child's emotional state. For example, if a child shows negative emotion in response to a question, that emotion is included in the answer. In addition, the emotion estimation function can be used to analyze a child's emotional response to a parent's question and reflect it in the answer, making it easier for parents to understand their child's emotional state. For example, if a child shows neutral emotion in response to a question, that emotion is included in the answer. In this way, a system is constructed that uses the emotion estimation function to analyze a child's emotional response to a parent's question and reflects it in the answer, making it easier for parents to understand their child's emotional state.

[0087] Convenience can be improved by adding a function that allows parents to input questions by voice. A system that improves convenience can be built by adding a function that allows parents to input questions by voice. For example, when a parent speaks a question into their smartphone, the generation AI analyzes the question and provides an answer. A voice input function is also provided, allowing parents to input questions by voice. For example, when a parent says, "Tell me about what happened at school today," the generation AI will respond to the question. Convenience can also be improved by adding a function that allows parents to input questions by voice. For example, it would allow parents to input questions by voice even when they are busy. This would improve convenience by allowing parents to input questions by voice.

[0088] Answers to questions can be provided in the form of visual notes or mind maps. A system can be built in which answers to questions are provided in visual note format, making it easier for parents to understand. For example, the answers can be shown in diagrams or illustrations. Answers to questions can also be provided in mind map format, making it easier for parents to organize information. For example, the answers can be visually displayed with related keywords or concepts. Answers can also be provided in the form of visual notes or mind maps, making it easier for parents to understand the answers intuitively. For example, the answers can be displayed in different colors. In this way, answers can be provided in the form of visual notes or mind maps, making it easier for parents to understand intuitively.

[0089] The emotion estimation function can be used to monitor a child's emotional reactions to a parent's questions in real time and optimize the content of the answers. A system is constructed that uses the emotion estimation function to monitor a child's emotional reactions to a parent's questions in real time and optimize the content of the answers. For example, if a child shows positive emotions, an answer that reflects that emotion is provided. Furthermore, by monitoring a child's emotional reactions to a parent's questions in real time and optimizing the content of the answers, it becomes easier for parents to understand their child's emotional state. For example, if a child shows negative emotions, an answer that reflects that emotion is provided. Furthermore, by using the emotion estimation function to monitor a child's emotional reactions to a parent's questions in real time and optimizing the content of the answers, it becomes easier for parents to understand their child's emotional state. For example, if a child shows neutral emotions, an answer that reflects that emotion is provided. In this way, by monitoring a child's emotional reactions to a parent's questions in real time and optimizing the content of the answers, it becomes easier for parents to understand their child's emotional state.

[0090] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0091] The device worn by the child is equipped with environmental sensors and can collect information about the surrounding environment. For example, the device may be equipped with a temperature sensor and can monitor the temperature of the environment in which the child is spending time. The device may also be equipped with a humidity sensor and can measure the humidity around the child. Furthermore, the device may be equipped with a noise sensor and can record the noise level in the child's location. This allows parents to understand the environment in which their child is spending time.

[0092] The device worn by the child is equipped with learning support functions and can monitor the child's learning status. For example, the device can record what the child is studying and track their learning progress. The device can also determine whether the child is concentrating while studying and notify parents of the level of concentration. Furthermore, the device can record any doubts or questions the child has while studying and notify parents. This allows parents to understand their child's learning status and provide appropriate support.

[0093] Devices worn by children are equipped with a function to monitor the amount of exercise, allowing parents to understand their children's exercise habits. For example, the device is equipped with a pedometer and can record the number of steps a child takes in a day. The device is also equipped with an acceleration sensor and can measure the amount of exercise a child performs. Furthermore, the device can use its GPS function to record the route a child takes when exercising. This allows parents to understand their children's exercise habits and use the information to help manage their health.

[0094] The device worn by the child is equipped with a sleep monitoring function to understand the child's sleep status. For example, the device can record the child's movements while sleeping and evaluate the quality of sleep. The device can also monitor the child's heart rate while sleeping using a heart rate sensor. Furthermore, the device is equipped with an audio sensor to record the child's snoring and talking in their sleep. This allows parents to understand their child's sleep status and take measures to improve it if necessary.

[0095] The device worn by the child can use its emotion estimation function to send an alert to the parent when the child feels a particular emotion. For example, it can notify the parent when the child feels strong anxiety. The device worn by the child can also use its emotion estimation function to send an alert to the parent when the child is in an excited state. For example, by notifying the parent when the child is excited, the parent can take appropriate action. The device worn by the child can also detect, for example, when the child feels sadness or anger, and send an alert to the parent. For example, it can notify the parent when the child is crying. This allows the parent to be notified when the child feels a particular emotion.

[0096] A device worn by a child can use an emotion estimation function to analyze the child's emotional state in real time and notify the parent. For example, the device can analyze the child's facial expressions to estimate the emotional state. For example, it can detect smiling or crying faces and notify the parent. The device can also use voice analysis technology to estimate the child's emotion from the tone and tempo of the child's voice. For example, it can detect emotions such as anger or sadness and send an alert to the parent. The device can also use biosensors to estimate the emotional state from the heart rate or galvanic skin response. For example, it can detect stress or excitement and notify the parent. This allows the child's emotional state to be understood in real time.

[0097] A device worn by a child can use an emotion estimation function to analyze the child's emotional state in real time and notify the parent. For example, the device can analyze the child's facial expressions to estimate the emotional state. For example, it can detect smiling or crying faces and notify the parent. The device can also use voice analysis technology to estimate the child's emotion from the tone and tempo of the child's voice. For example, it can detect emotions such as anger or sadness and send an alert to the parent. The device can also use biosensors to estimate the emotional state from the heart rate or galvanic skin response. For example, it can detect stress or excitement and notify the parent. This allows the child's emotional state to be understood in real time.

[0098] A device worn by a child can use an emotion estimation function to analyze the child's emotional state in real time and notify the parent. For example, the device can analyze the child's facial expressions to estimate the emotional state. For example, it can detect smiling or crying faces and notify the parent. The device can also use voice analysis technology to estimate the child's emotion from the tone and tempo of the child's voice. For example, it can detect emotions such as anger or sadness and send an alert to the parent. The device can also use biosensors to estimate the emotional state from the heart rate or galvanic skin response. For example, it can detect stress or excitement and notify the parent. This allows the child's emotional state to be understood in real time.

[0099] A device worn by a child can use an emotion estimation function to analyze the child's emotional state in real time and notify the parent. For example, the device can analyze the child's facial expressions to estimate the emotional state. For example, it can detect smiling or crying faces and notify the parent. The device can also use voice analysis technology to estimate the child's emotion from the tone and tempo of the child's voice. For example, it can detect emotions such as anger or sadness and send an alert to the parent. The device can also use biosensors to estimate the emotional state from the heart rate or galvanic skin response. For example, it can detect stress or excitement and notify the parent. This allows the child's emotional state to be understood in real time.

[0100] A device worn by a child can use an emotion estimation function to analyze the child's emotional state in real time and notify the parent. For example, the device can analyze the child's facial expressions to estimate the emotional state. For example, it can detect smiling or crying faces and notify the parent. The device can also use voice analysis technology to estimate the child's emotion from the tone and tempo of the child's voice. For example, it can detect emotions such as anger or sadness and send an alert to the parent. The device can also use biosensors to estimate the emotional state from the heart rate or galvanic skin response. For example, it can detect stress or excitement and notify the parent. This allows the child's emotional state to be understood in real time.

[0101] The processing flow of the second embodiment will be briefly explained below.

[0102] Step 1: The device worn by the child collects the child's speech and conversation. For example, the device analyzes the child's speech and conversation in real time and extracts important information. The device is also designed to be lightweight and easy to carry, so that children can use it comfortably in their daily lives. Step 2: The generation AI analyzes the data of the child's utterances and conversations and generates a summary. For example, the generation AI may use a text generation AI (e.g., LLM) to summarize the content of the utterances and conversations. The generation AI may also use a multimodal generation AI to summarize the content of the utterances and conversations. The generation AI may also extract key points and generate a summary. Step 3: The notification unit notifies the parent's smartphone of the summary generated by the generation AI. For example, the parent's smartphone can receive the summary via push notification. Alternatively, the parent's smartphone can receive the summary via email notification. Alternatively, the parent's smartphone can check the summary through a dedicated app.

[0103] 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.

[0104] 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> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). 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 speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. 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. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0105] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0106] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0107] 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0108] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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 and / or a LAN.

[0109] 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.

[0110] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0111] 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 user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0112] 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.

[0113] 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.

[0114] 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.

[0115] 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. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0116] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0117] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0118] 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.

[0119] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. 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. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0120] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0121] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0122] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0123] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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 and / or a LAN.

[0124] 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.

[0125] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0126] 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 user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0127] 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.

[0128] 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.

[0129] 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.

[0130] 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. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0131] In the headset type terminal 314, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0132] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0133] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0134] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. 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. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0135] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0136] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0137] 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0138] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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 and / or a LAN.

[0139] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0140] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0141] 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 image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0142] 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.

[0143] The control object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0144] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0145] 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.

[0146] 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. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0147] In the robot 414, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The robot 414 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0148] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0149] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice 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 voice data.

[0150] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. 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. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0151] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0152] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0153] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0154] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0155] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0156] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0157] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0158] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0159] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0160] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0161] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0162] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0163] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0164] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0165] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0166] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0167] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0168] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0169] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0170] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. A device worn by the child, A generation AI that analyzes data on utterances and conversations collected by the device attached to the child and generates a summary; a notification unit that notifies the parent's smartphone of the summary generated by the generation AI. A system characterized by:

2. The device worn by the child comprises: It is a wristwatch or pendant type.

2. The system of claim 1.

3. The device worn by the child comprises: Equipped with biosensors to monitor children's health 2. The system of claim 1.

4. The device worn by the child comprises: Equipped with a GPS function, it notifies parents of their child's location in real time.

2. The system of claim 1.

5. The device worn by the child comprises: Equipped with an emotion estimation function, it analyzes the child's emotional state in real time and notifies the parent.

2. The system of claim 1.

6. The device worn by the child comprises: Built into clothing 2. The system of claim 1.

7. The device worn by the child comprises: It is worn by multiple children and analyzes group conversations and activities.

2. The system of claim 1.

8. The device worn by the child comprises: Alerts the parent when the child experiences a particular emotion 2. The system of claim 1.

Images