system

Abstract

The system according to this embodiment aims to automatically record a child's daily life and provide personalized childcare advice. [Solution] The system according to the embodiment comprises a recording unit, an advice unit, a communication unit, and a storage unit. The recording unit automatically records the child's life. The advice unit provides advice based on the data recorded by the recording unit. The communication unit automatically contacts the hospital based on the advice provided by the advice unit. The storage unit automatically edits and saves the data recorded by the recording unit.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the prior art, there is a problem that it is laborious to record a child's life and provide childcare advice, and it is difficult to provide individualized responses.

[0005] The system according to the embodiment aims to automatically record a child's life and provide individualized childcare advice.

Means for Solving the Problems

[0006] The system according to this embodiment comprises a recording unit, an advice unit, a communication unit, and a storage unit. The recording unit automatically records the child's daily life. The advice unit provides advice based on the data recorded by the recording unit. The communication unit automatically contacts the hospital based on the advice provided by the advice unit. The storage unit automatically edits and saves the data recorded by the recording unit. [Effects of the Invention]

[0007] The system according to this embodiment can automatically record a child's daily life and provide personalized childcare advice. [Brief explanation of the drawing]

[0008] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Modes for carrying out the invention]

[0009] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0010] First, let's explain the terminology used in the following explanation.

[0011] In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), or TPU (Tensor Processing Unit).

[0012] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0013] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0014] In the following embodiments, the numbered communication I / F (Interface) is an interface including a communication processor, an antenna, and the like. The communication I / F controls communication between a plurality of computers. Examples of communication standards applied to the communication I / F include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B". That is, "A and / or B" means that it may be only A, only B, or a combination of A and B. Also, in this specification, when expressing three or more matters connected by "and / or", the same concept as "A and / or B" is applied.

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

[0017] As shown in FIG. 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[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, the RAM 30, and the storage 32 are connected to a bus 34. Also, the database 24 and the communication I / F 26 are 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 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0020] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, and accepts user input. The touch panel 38A accepts user input via touch by detecting contact with an object (e.g., a pen or finger). The microphone 38B accepts user input via voice by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 (see Figure 2) acquires the data indicating the user input.

[0021] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user by outputting the data in a form perceptible to the user (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0024] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0025] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0026] In the smart device 14, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used in conjunction 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 a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart device 14 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0027] Furthermore, other devices besides the data processing device 12 may also 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 processing results (such as prediction results) using the data generation model 58 by communicating with the server device having the data generation model 58. The data processing device 12 may also be a server device or a terminal device owned by a user (e.g., a mobile phone, robot, home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example of form 1) The childcare support system according to an embodiment of the present invention is a system that utilizes generative AI to solve the "I don't know, what should I do?" problem in childcare. This childcare support system reduces the burden on parents by automatically recording the child's life, providing advice, automatically contacting hospitals, and saving data. First, the childcare support system automatically records the child's daily life, such as sleep, milk, and meals. This is done through camera photography and automatically recorded on a platform such as Notion. Next, the childcare support system provides voice advice on how to deal with the child when they cry or are unwell. The generative AI analyzes what kind of coping methods worked for children with similar personalities, behaviors, and characteristics to the parent's child and proposes solutions by combining this with the parent's child's data. For example, it provides specific advice such as, "This child has the personality of XX, so this method to prevent night crying would be good." In addition, if there is a problem with the crying, the childcare support system automatically contacts a hospital. This decision is also made by the generative AI, supporting parents so that they can concentrate on caring for their child. Furthermore, the childcare support system automatically edits and saves the captured data, allowing it to be preserved as memories. This ensures that even smiles that might otherwise be missed are saved. For example, the childcare support system includes a recording unit that automatically records the child's daily life. The recording unit automatically records the child's life through camera photography. Next, the childcare support system includes an advice unit that provides advice based on the data recorded by the recording unit. The advice unit uses generative AI to analyze what coping strategies worked for children with similar personalities, behaviors, and characteristics to the parent's child, and provides advice by combining this with the parent's child's data. Furthermore, the childcare support system includes a contact unit that automatically contacts a hospital based on the advice provided by the advice unit. The contact unit automatically contacts a hospital if there is a problem with the child's crying. Finally, the childcare support system includes a storage unit that automatically edits and saves the data recorded by the recording unit. The storage unit automatically edits and saves the data recorded by the recording unit. In this way, the childcare support system can reduce the burden on parents and support the child's development.

[0029] The childcare support system according to this embodiment comprises a recording unit, an advice unit, a communication unit, and a storage unit. The recording unit automatically records the child's life. The recording unit automatically records the child's life, for example, by taking pictures with a camera. The recording unit can record based on, for example, the camera's resolution and the timing of the shot. The recording unit can collect more detailed data the higher the camera's resolution. The recording unit can record important moments without missing them by adjusting the timing of the shot. The advice unit provides advice based on the data recorded by the recording unit. The advice unit uses, for example, a generative AI to analyze what coping methods worked for children with similar personalities, behaviors, and characteristics to the user's child, and provides advice by combining this with the user's child's data. The advice unit uses, for example, a generative AI to provide specific advice such as, "This child has the personality of XX, so this method of preventing night crying would be good." The advice unit can use, for example, a generative AI to provide optimal advice based on past data. The advice unit can use, for example, a generative AI to analyze data in real time and provide advice immediately. The liaison unit automatically contacts the hospital based on the advice provided by the advice unit. The liaison unit automatically contacts the hospital, for example, if there is a problem with the baby's crying. The liaison unit can contact the hospital, for example, based on the crying pattern or the method of voice analysis. The liaison unit can analyze the crying pattern and contact the hospital if there is an abnormality. The liaison unit can detect abnormalities in crying using voice analysis technology and contact the hospital. The storage unit automatically edits and saves the data recorded by the recording unit. The storage unit automatically edits and saves the data recorded by the recording unit. The storage unit can save the data, for example, based on editing criteria and saving format. The storage unit can set editing criteria and prioritize saving important data. The storage unit can select a saving format and save the data in an appropriate format. As a result, the childcare support system according to the embodiment can reduce the burden on parents and support the child's development.

[0030] The recording unit automatically records the child's life. For example, it automatically records the child's life through camera recording. Specifically, the camera captures high-resolution video, allowing for detailed recording of the child's movements and expressions. The camera is installed in the child's living space and automatically takes pictures at regular intervals. For example, the camera takes pictures every hour, recording the child's daily activities chronologically. Furthermore, the camera is equipped with motion detection, automatically detecting and taking pictures the moment the child moves. This ensures that important moments are not missed. The camera's resolution is also adjustable, allowing for detailed recording of the child's expressions and movements at high resolution. For example, using a 4K resolution camera allows for clear recording of subtle changes in the child's expressions and movements. Additionally, the recording unit transmits the recorded video to a cloud server in real time, securely storing the data. This allows parents to check on their child's life anytime, anywhere via smartphone or computer. The recording unit also allows for adjustment of the recording timing, enabling focus on recording specific events or activities. For example, important moments such as mealtimes and playtimes can be recorded without missing any. This allows the recording unit to record the child's life in detail and accurately, providing valuable information for parents.

[0031] The advice unit provides advice based on data recorded by the recording unit. For example, the advice unit uses a generative AI to analyze what coping strategies worked for children with similar personalities, behaviors, and characteristics to the parent's child, and combines this with the parent's own child's data to provide advice. Specifically, the generative AI analyzes video and behavioral data provided by the recording unit to identify the child's personality and behavioral patterns. For example, the generative AI infers the child's emotional state from their facial expressions and movements, and analyzes the causes and coping strategies for nighttime crying. The generative AI refers to past databases to identify effective coping strategies for children with similar personalities and behavioral patterns. For example, it provides specific advice such as, "This child has the personality trait of XX, so this method of preventing nighttime crying would be good." Furthermore, the generative AI can analyze data in real time and provide advice immediately. For example, the moment a child starts crying at night, the generative AI notifies the parent of the appropriate coping strategy. This allows the parent to respond quickly and increases the child's sense of security. The generative AI can also provide optimal advice based on past data. For example, it analyzes past nighttime crying data to identify specific patterns and causes. This allows parents to develop long-term strategies and support their child's development. The advice department can provide parents with reliable information and reduce the burden of childcare.

[0032] The liaison unit automatically contacts the hospital based on advice provided by the advisory unit. For example, the liaison unit automatically contacts the hospital if there is a problem with the baby's crying. Specifically, the liaison unit analyzes crying data provided by the recording unit and detects abnormal patterns. For example, it analyzes crying audio data and detects unusually high-pitched or prolonged crying. The liaison unit can use voice analysis technology to detect abnormalities in crying and contact the hospital. For example, it can analyze crying patterns and contact the hospital if there is an abnormality. The liaison unit can send data on the child's crying and information provided by the advisory unit to the hospital, prompting a quick response. This allows the hospital to understand the child's condition and take appropriate action. The liaison unit also notifies the parents that a contact has been made with the hospital. This allows parents to monitor their child's condition with peace of mind. Furthermore, the liaison unit strengthens collaboration with the hospital, enabling a quicker response. For example, it can integrate with the hospital's system and share the child's data in real time. This allows the hospital to constantly monitor the child's condition and take appropriate action. The liaison department plays a crucial role in ensuring smooth communication between parents and hospitals and protecting children's health.

[0033] The storage unit automatically edits and saves data recorded by the recording unit. Specifically, the storage unit analyzes recorded video and audio data and extracts important moments. For example, it can automatically detect and edit important moments for parents, such as a child's first steps or first words. The storage unit can set editing criteria and prioritize saving important data. For example, it can prioritize saving data related to specific events or activities, while compressing and saving everyday data. This allows the storage unit to efficiently manage data storage capacity. The storage unit can also select the saving format and save data in an appropriate format. For example, it can save video data in high resolution and audio data in a compressed format. This allows the storage unit to optimize storage capacity while maintaining data quality. Furthermore, the storage unit can back up saved data to a cloud server, ensuring data security. This allows parents to save data with peace of mind without worrying about data loss. The storage unit plays a vital role in safely and efficiently saving precious memories for parents and recording their children's growth.

[0034] The recording unit can automatically record a child's life through camera photography. The recording unit can record based on, for example, the camera's resolution and the timing of the shot. For example, the higher the camera's resolution, the more detailed the data the recording unit can collect. For example, the recording unit can record important moments without missing them by adjusting the timing of the shot. This allows for the collection of detailed data by automatically recording a child's life through camera photography. Some or all of the above-described processes in the recording unit may be performed using, for example, AI, or not using AI. For example, the recording unit can input image data captured by the camera into a generating AI and have the generating AI perform the conversion of the image data into text data.

[0035] The advice unit can use generative AI to analyze what coping strategies worked for children with similar personalities, behaviors, and characteristics to the user's own child, and then combine this with the user's own child's data to provide advice. For example, the advice unit's generative AI can provide specific advice such as, "This child has the personality of XX, so this method of preventing night crying would be good." The advice unit's generative AI can provide optimal advice based on past data. The advice unit's generative AI can analyze data in real time and provide advice immediately. This allows for the provision of personalized advice by using generative AI. Some or all of the above-described processes in the advice unit may be performed using generative AI, or they may not be performed using generative AI. For example, the advice unit can input the child's data into the generative AI, and the generative AI can generate optimal advice based on past data.

[0036] The communication unit can automatically contact a hospital if there is a problem with the baby's crying. The communication unit can make contact based, for example, on crying patterns or methods of voice analysis. For example, the communication unit can analyze crying patterns and contact a hospital if there is an abnormality. For example, the communication unit can use voice analysis technology to detect abnormalities in crying and contact a hospital. This enables a quick response by automatically contacting a hospital when there is a problem with the baby's crying. Some or all of the above processing in the communication unit may be performed using AI, for example, or without AI. For example, the communication unit can input crying voice data into a generating AI, and if the generating AI detects an abnormality, it can contact a hospital.

[0037] The storage unit can automatically edit and save the data recorded by the recording unit. The storage unit can save the data based on editing criteria and saving format, for example. The storage unit can set editing criteria and prioritize saving important data. The storage unit can select a saving format and save the data in an appropriate format, for example. This makes it easy to save memories by automatically editing and saving the recorded data. Some or all of the above-described processes in the storage unit may be performed using AI, for example, or without AI. For example, the storage unit can input the recorded data into a generating AI, which can then edit and save the data.

[0038] The recording unit can simultaneously acquire biometric information such as the child's body temperature and heart rate during recording. For example, the recording unit can use a sensor linked to a camera to record the child's body temperature in real time. For example, the recording unit can monitor the child's heart rate and issue an alert if there is an abnormality. For example, the recording unit can measure the child's respiratory rate and record their health status in detail. This allows for a detailed understanding of the child's health status by simultaneously acquiring biometric information such as body temperature and heart rate. Some or all of the above-described processes in the recording unit may be performed using AI, for example, or without AI. For example, the recording unit can input biometric information acquired by sensors into a generating AI, which can then analyze the health status.

[0039] The recording unit can record ambient sounds and temperature around the child during recording, allowing it to understand changes in the living environment. For example, the recording unit can record ambient sounds and analyze factors that affect the child's sleep patterns. For example, the recording unit can record room temperature and collect data for appropriate temperature control. For example, the recording unit can record lighting brightness and provide an environment suitable for the child's activities. In this way, changes in the living environment can be understood by recording ambient sounds and temperature around the child. Some or all of the above processing in the recording unit may be performed using AI, for example, or without AI. For example, the recording unit can input ambient sound and temperature data into a generating AI, which can then analyze changes in the living environment.

[0040] The recording unit can simultaneously record the parent's voice and facial expressions during recording, allowing for analysis of parent-child interactions. For example, the recording unit can analyze the tone of the parent's voice and record the child's response. For example, the recording unit can capture the parent's facial expressions with a camera and analyze their relationship to the child's emotions. For example, the recording unit can transcribe the content of the parent-child conversation into text and analyze the interaction patterns. In this way, parent-child interactions can be analyzed by recording the parent's voice and facial expressions. Some or all of the above processing in the recording unit may be performed using AI, for example, or without AI. For example, the recording unit can input the parent's voice and facial expression data into a generating AI, which can then analyze the parent-child interaction.

[0041] The recording unit can record a child's play and learning activities during recording, allowing for a detailed understanding of their developmental process. For example, the recording unit can videotape a child playing and analyze their developmental process. For example, the recording unit can record a child's learning activities to track their learning progress. For example, the recording unit can record a child's creative activities to help discover their talents. In this way, by recording a child's play and learning activities, a detailed understanding of their developmental process can be obtained. Some or all of the above-described processes in the recording unit may be performed using AI, for example, or without AI. For example, the recording unit can input play and learning activities into a generating AI, which can then analyze the developmental process.

[0042] The advice unit can select the most appropriate advice by referring to past advice history when providing advice. For example, the advice unit may prioritize providing advice that has been effective in the past. For example, the advice unit may analyze past advice history and select highly effective advice. For example, the advice unit may provide advice tailored to the child's development based on past advice history. In this way, the advice unit can provide the most appropriate advice by referring to past advice history. Some or all of the above processes in the advice unit may be performed using, for example, a generative AI, or without a generative AI. For example, the advice unit may input past advice history into a generative AI, which can then select the most appropriate advice.

[0043] The advice unit can apply different advice algorithms depending on the child's developmental stage when providing advice. For example, the advice unit provides advice on sleep and breastfeeding during the neonatal period. For example, the advice unit provides advice on play and learning during the toddler period. For example, the advice unit provides advice on school life and peer relationships during the school-age period. By applying different advice algorithms according to the child's developmental stage, appropriate advice can be provided according to their growth. Some or all of the above processing in the advice unit may be performed using, for example, a generative AI, or without a generative AI. For example, the advice unit can input child developmental stage data into a generative AI, and the generative AI can apply an advice algorithm appropriate to the developmental stage.

[0044] The advice unit can adjust the way it expresses advice, taking into account the parent's stress level, when providing advice. For example, if the parent is stressed, the advice unit will provide concise and easy-to-understand advice. For example, if the parent is relaxed, the advice unit will provide detailed advice. For example, if the parent is tired, the advice unit will provide advice that includes words of encouragement. In this way, by adjusting the way the advice is expressed, taking into account the parent's stress level, the advice unit can provide advice that is easy for the parent to understand. Some or all of the above processing in the advice unit may be performed using, for example, a generative AI, or not using a generative AI. For example, the advice unit can input the parent's stress level data into a generative AI, and the generative AI can adjust the way the advice is expressed according to the stress level.

[0045] The advice unit can adjust the timing of advice based on the child's daily rhythm when providing advice. For example, the advice unit can provide advice to help the child relax before going to sleep. For example, the advice unit can provide advice to help the child become active after waking up. For example, the advice unit can provide advice to stimulate the child's appetite before meals. By adjusting the timing of advice based on the child's daily rhythm, advice can be provided at the appropriate time. Some or all of the above processing in the advice unit may be performed using, for example, a generative AI, or without a generative AI. For example, the advice unit can input the child's daily rhythm data into a generative AI, which can then adjust the timing of advice based on the daily rhythm.

[0046] The liaison unit can record the child's health status in detail when contacting a medical institution, thereby enriching the information provided. For example, the liaison unit can record the child's body temperature and heart rate and provide it to the medical institution. For example, the liaison unit can record the child's symptoms in detail and provide it to the medical institution. For example, the liaison unit can refer to the child's past health history and provide it to the medical institution. This allows for appropriate medical care by recording the child's health status in detail and enriching the information provided to the medical institution. Some or all of the above processes in the liaison unit may be performed using AI, for example, or not using AI. For example, the liaison unit can input health status data into a generating AI, which can then analyze the data and generate information to provide to the medical institution.

[0047] The communication unit can select a communication method when contacting a parent, taking into account the parent's current situation (e.g., whether they are at work). For example, if the parent is at work, the communication unit will contact them via email or message. If the parent is at home, the communication unit will contact them by phone. If the parent is out, the communication unit will contact them via app notification. By selecting a communication method that takes the parent's current situation into account, the communication unit can provide the parent with the most suitable means of communication. Some or all of the above processing in the communication unit may be performed using AI, for example, or not. For example, the communication unit can input data on the parent's current situation into a generating AI, which can then select the most suitable communication method according to the situation.

[0048] The liaison department can select the most suitable contact when making a contact by referring to the medical institution's past response history. For example, the liaison department may prioritize selecting medical institutions that have been handled in the past. For example, the liaison department may analyze past response history and select the most suitable medical institution. For example, the liaison department may select a specialist based on past response history. In this way, the most suitable contact can be selected by referring to the medical institution's past response history. Some or all of the above processes in the liaison department may be performed using AI, for example, or not using AI. For example, the liaison department may input past response history data of medical institutions into a generating AI, and the generating AI can select the most suitable contact.

[0049] The liaison unit can transmit data about the child's health status to medical institutions in real time when contact is made. For example, the liaison unit can transmit the child's body temperature and heart rate in real time. For example, the liaison unit can transmit the child's symptoms in real time. For example, the liaison unit can transmit the child's past health history in real time. This enables a rapid medical response by transmitting data about the child's health status in real time. Some or all of the above processing in the liaison unit may be performed using AI, for example, or not using AI. For example, the liaison unit can input health status data into a generating AI, the generating AI can analyze the data, and transmit it to medical institutions in real time.

[0050] The storage unit can determine the priority of saving data based on its importance. For example, the storage unit might prioritize saving data for important events (such as birthdays). For example, it might save everyday data at an appropriate rate. For example, the storage unit might automatically delete unnecessary data. This allows important data to be saved preferentially by determining the priority of saving based on its importance. Some or all of the above processes in the storage unit may be performed using AI, for example, or without AI. For example, the storage unit can input the importance of the data into a generating AI, which can then determine the priority of saving.

[0051] The storage unit can record the editing history of the data when it is saved, allowing users to review the edits later. For example, the storage unit can record the editing history of the data with a timestamp. For example, the storage unit can record the edits in detail so that they can be reviewed later. For example, the storage unit can make the editing history searchable so that specific edits can be quickly reviewed. This allows users to review the edits later by recording the editing history of the data. Some or all of the above processes in the storage unit may be performed using AI, for example, or without AI. For example, the storage unit can input the editing history data into a generating AI, which can then record and review the edits.

[0052] The storage unit can ensure data security by automatically backing up data during storage. For example, the storage unit can periodically save data backups to the cloud. For example, the storage unit can ensure data security by saving data backups in multiple locations. For example, the storage unit can enhance security by encrypting and saving data backups. This ensures data security by automatically backing up data. Some or all of the above processes in the storage unit may be performed using AI, for example, or without AI. For example, the storage unit can input backup data into a generating AI, which can then manage the backups.

[0053] The storage unit can save data to the cloud and make it accessible from multiple devices. For example, the storage unit can save data to the cloud and make it accessible from smartphones and tablets. For example, the storage unit can save data to the cloud and make it accessible to all family members. For example, the storage unit can save data to the cloud and make it accessible even when away from home. This makes the data accessible from multiple devices by saving it to the cloud. Some or all of the above processing in the storage unit may be performed using AI, for example, or not using AI. For example, the storage unit can input cloud data into a generating AI, and the generating AI can manage the data.

[0054] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0055] The childcare support system can also include a learning section that provides learning content tailored to the child's developmental stage. The learning section, for example, selects and provides appropriate learning content according to the child's age and developmental stage. For instance, during early childhood, the learning section might provide games to promote the recognition of colors and shapes. For instance, during elementary school, the learning section might provide materials for learning the basics of arithmetic and reading and writing. The learning section could also create and provide individualized learning plans based on the child's interests and concerns. This allows for support of the child's intellectual development by providing learning content appropriate to their developmental stage.

[0056] Childcare support systems can also include a social interaction section to foster children's social skills. This section could, for example, provide event information to offer children opportunities to play with other children. It could also provide community features to promote interaction among parents. Furthermore, it could suggest group activities and workshops to cultivate children's social skills. Finally, it could offer online games and activities for children to play cooperatively with other children. This provides opportunities to foster children's social skills and supports their development.

[0057] The childcare support system could also include an education department that provides educational content to improve parents' childcare skills. For example, the education department could provide the latest research and information on childcare. For example, it could provide videos and articles explaining childcare methods appropriate to a child's developmental stage. For example, it could provide Q&A sessions to help parents resolve their questions and concerns about childcare. For example, it could offer online courses and workshops on childcare. This would allow parents to approach childcare with greater confidence by providing educational content to improve their childcare skills.

[0058] Childcare support systems can also include a sharing section for parents to share their childcare experiences. This sharing section could, for example, provide a platform for parents to share their successes and failures with other parents. It could also allow parents to post advice and tips on childcare, ask questions about childcare and receive answers from other parents, or share photos and videos related to childcare and interact with other parents. This allows parents to learn from each other and improve the quality of their childcare by sharing their experiences.

[0059] The childcare support system can also include a resources section that provides resources to deepen parents' knowledge of childcare. For example, the resources section could provide specialized books and articles on childcare. For example, it could provide the latest research findings and news on childcare. For example, it could provide an online library on childcare that parents can freely access. For example, it could provide interviews and lectures by childcare experts. By providing resources to deepen parents' knowledge of childcare, it enables parents to engage in childcare more effectively.

[0060] The following briefly describes the processing flow for example form 1.

[0061] Step 1: The recording unit automatically records the child's life. For example, it records the child's life through taking pictures with a camera and collects detailed data based on the camera's resolution and the timing of the shots. Step 2: The advice unit provides advice based on the data recorded by the recording unit. For example, it uses a generative AI to analyze the optimal approach based on the child's personality, behavior, and characteristics, and provides specific advice. Step 3: The liaison unit automatically contacts the hospital based on the advice provided by the advisory unit. For example, if there is a problem with the baby's crying, the unit uses crying patterns and voice analysis technology to detect the abnormality and contacts the hospital. Step 4: The storage unit automatically edits and saves the data recorded by the recording unit. For example, it saves the data in an appropriate format based on editing criteria and saving format, and prioritizes saving important data.

[0062] (Example of form 2) The childcare support system according to an embodiment of the present invention is a system that utilizes generative AI to solve the "I don't know, what should I do?" problem in childcare. This childcare support system reduces the burden on parents by automatically recording the child's life, providing advice, automatically contacting hospitals, and saving data. First, the childcare support system automatically records the child's daily life, such as sleep, milk, and meals. This is done through camera photography and automatically recorded on a platform such as Notion. Next, the childcare support system provides voice advice on how to deal with the child when they cry or are unwell. The generative AI analyzes what kind of coping methods worked for children with similar personalities, behaviors, and characteristics to the parent's child and proposes solutions by combining this with the parent's child's data. For example, it provides specific advice such as, "This child has the personality of XX, so this method to prevent night crying would be good." In addition, if there is a problem with the crying, the childcare support system automatically contacts a hospital. This decision is also made by the generative AI, supporting parents so that they can concentrate on caring for their child. Furthermore, the childcare support system automatically edits and saves the captured data, allowing it to be preserved as memories. This ensures that even smiles that might otherwise be missed are saved. For example, the childcare support system includes a recording unit that automatically records the child's daily life. The recording unit automatically records the child's life through camera photography. Next, the childcare support system includes an advice unit that provides advice based on the data recorded by the recording unit. The advice unit uses generative AI to analyze what coping strategies worked for children with similar personalities, behaviors, and characteristics to the parent's child, and provides advice by combining this with the parent's child's data. Furthermore, the childcare support system includes a contact unit that automatically contacts a hospital based on the advice provided by the advice unit. The contact unit automatically contacts a hospital if there is a problem with the child's crying. Finally, the childcare support system includes a storage unit that automatically edits and saves the data recorded by the recording unit. The storage unit automatically edits and saves the data recorded by the recording unit. In this way, the childcare support system can reduce the burden on parents and support the child's development.

[0063] The childcare support system according to this embodiment comprises a recording unit, an advice unit, a communication unit, and a storage unit. The recording unit automatically records the child's life. The recording unit automatically records the child's life, for example, by taking pictures with a camera. The recording unit can record based on, for example, the camera's resolution and the timing of the shot. The recording unit can collect more detailed data the higher the camera's resolution. The recording unit can record important moments without missing them by adjusting the timing of the shot. The advice unit provides advice based on the data recorded by the recording unit. The advice unit uses, for example, a generative AI to analyze what coping methods worked for children with similar personalities, behaviors, and characteristics to the user's child, and provides advice by combining this with the user's child's data. The advice unit uses, for example, a generative AI to provide specific advice such as, "This child has the personality of XX, so this method of preventing night crying would be good." The advice unit can use, for example, a generative AI to provide optimal advice based on past data. The advice unit can use, for example, a generative AI to analyze data in real time and provide advice immediately. The liaison unit automatically contacts the hospital based on the advice provided by the advice unit. The liaison unit automatically contacts the hospital, for example, if there is a problem with the baby's crying. The liaison unit can contact the hospital, for example, based on the crying pattern or the method of voice analysis. The liaison unit can analyze the crying pattern and contact the hospital if there is an abnormality. The liaison unit can detect abnormalities in crying using voice analysis technology and contact the hospital. The storage unit automatically edits and saves the data recorded by the recording unit. The storage unit automatically edits and saves the data recorded by the recording unit. The storage unit can save the data, for example, based on editing criteria and saving format. The storage unit can set editing criteria and prioritize saving important data. The storage unit can select a saving format and save the data in an appropriate format. As a result, the childcare support system according to the embodiment can reduce the burden on parents and support the child's development.

[0064] The recording unit automatically records the child's life. For example, it automatically records the child's life through camera recording. Specifically, the camera captures high-resolution video, allowing for detailed recording of the child's movements and expressions. The camera is installed in the child's living space and automatically takes pictures at regular intervals. For example, the camera takes pictures every hour, recording the child's daily activities chronologically. Furthermore, the camera is equipped with motion detection, automatically detecting and taking pictures the moment the child moves. This ensures that important moments are not missed. The camera's resolution is also adjustable, allowing for detailed recording of the child's expressions and movements at high resolution. For example, using a 4K resolution camera allows for clear recording of subtle changes in the child's expressions and movements. Additionally, the recording unit transmits the recorded video to a cloud server in real time, securely storing the data. This allows parents to check on their child's life anytime, anywhere via smartphone or computer. The recording unit also allows for adjustment of the recording timing, enabling focus on recording specific events or activities. For example, important moments such as mealtimes and playtimes can be recorded without missing any. This allows the recording unit to record the child's life in detail and accurately, providing valuable information for parents.

[0065] The advice unit provides advice based on data recorded by the recording unit. For example, the advice unit uses a generative AI to analyze what coping strategies worked for children with similar personalities, behaviors, and characteristics to the parent's child, and combines this with the parent's own child's data to provide advice. Specifically, the generative AI analyzes video and behavioral data provided by the recording unit to identify the child's personality and behavioral patterns. For example, the generative AI infers the child's emotional state from their facial expressions and movements, and analyzes the causes and coping strategies for nighttime crying. The generative AI refers to past databases to identify effective coping strategies for children with similar personalities and behavioral patterns. For example, it provides specific advice such as, "This child has the personality trait of XX, so this method of preventing nighttime crying would be good." Furthermore, the generative AI can analyze data in real time and provide advice immediately. For example, the moment a child starts crying at night, the generative AI notifies the parent of the appropriate coping strategy. This allows the parent to respond quickly and increases the child's sense of security. The generative AI can also provide optimal advice based on past data. For example, it analyzes past nighttime crying data to identify specific patterns and causes. This allows parents to develop long-term strategies and support their child's development. The advice department can provide parents with reliable information and reduce the burden of childcare.

[0066] The liaison unit automatically contacts the hospital based on advice provided by the advisory unit. For example, the liaison unit automatically contacts the hospital if there is a problem with the baby's crying. Specifically, the liaison unit analyzes crying data provided by the recording unit and detects abnormal patterns. For example, it analyzes crying audio data and detects unusually high-pitched or prolonged crying. The liaison unit can use voice analysis technology to detect abnormalities in crying and contact the hospital. For example, it can analyze crying patterns and contact the hospital if there is an abnormality. The liaison unit can send data on the child's crying and information provided by the advisory unit to the hospital, prompting a quick response. This allows the hospital to understand the child's condition and take appropriate action. The liaison unit also notifies the parents that a contact has been made with the hospital. This allows parents to monitor their child's condition with peace of mind. Furthermore, the liaison unit strengthens collaboration with the hospital, enabling a quicker response. For example, it can integrate with the hospital's system and share the child's data in real time. This allows the hospital to constantly monitor the child's condition and take appropriate action. The liaison department plays a crucial role in ensuring smooth communication between parents and hospitals and protecting children's health.

[0067] The storage unit automatically edits and saves data recorded by the recording unit. Specifically, the storage unit analyzes recorded video and audio data and extracts important moments. For example, it can automatically detect and edit important moments for parents, such as a child's first steps or first words. The storage unit can set editing criteria and prioritize saving important data. For example, it can prioritize saving data related to specific events or activities, while compressing and saving everyday data. This allows the storage unit to efficiently manage data storage capacity. The storage unit can also select the saving format and save data in an appropriate format. For example, it can save video data in high resolution and audio data in a compressed format. This allows the storage unit to optimize storage capacity while maintaining data quality. Furthermore, the storage unit can back up saved data to a cloud server, ensuring data security. This allows parents to save data with peace of mind without worrying about data loss. The storage unit plays a vital role in safely and efficiently saving precious memories for parents and recording their children's growth.

[0068] The recording unit can automatically record a child's life through camera photography. The recording unit can record based on, for example, the camera's resolution and the timing of the shot. For example, the higher the camera's resolution, the more detailed the data the recording unit can collect. For example, the recording unit can record important moments without missing them by adjusting the timing of the shot. This allows for the collection of detailed data by automatically recording a child's life through camera photography. Some or all of the above-described processes in the recording unit may be performed using, for example, AI, or not using AI. For example, the recording unit can input image data captured by the camera into a generating AI and have the generating AI perform the conversion of the image data into text data.

[0069] The advice unit can use generative AI to analyze what coping strategies worked for children with similar personalities, behaviors, and characteristics to the user's own child, and then combine this with the user's own child's data to provide advice. For example, the advice unit's generative AI can provide specific advice such as, "This child has the personality of XX, so this method of preventing night crying would be good." The advice unit's generative AI can provide optimal advice based on past data. The advice unit's generative AI can analyze data in real time and provide advice immediately. This allows for the provision of personalized advice by using generative AI. Some or all of the above-described processes in the advice unit may be performed using generative AI, or they may not be performed using generative AI. For example, the advice unit can input the child's data into the generative AI, and the generative AI can generate optimal advice based on past data.

[0070] The communication unit can automatically contact a hospital if there is a problem with the baby's crying. The communication unit can make contact based, for example, on crying patterns or methods of voice analysis. For example, the communication unit can analyze crying patterns and contact a hospital if there is an abnormality. For example, the communication unit can use voice analysis technology to detect abnormalities in crying and contact a hospital. This enables a quick response by automatically contacting a hospital when there is a problem with the baby's crying. Some or all of the above processing in the communication unit may be performed using AI, for example, or without AI. For example, the communication unit can input crying voice data into a generating AI, and if the generating AI detects an abnormality, it can contact a hospital.

[0071] The storage unit can automatically edit and save the data recorded by the recording unit. The storage unit can save the data based on editing criteria and saving format, for example. The storage unit can set editing criteria and prioritize saving important data. The storage unit can select a saving format and save the data in an appropriate format, for example. This makes it easy to save memories by automatically editing and saving the recorded data. Some or all of the above-described processes in the storage unit may be performed using AI, for example, or without AI. For example, the storage unit can input the recorded data into a generating AI, which can then edit and save the data.

[0072] The recording unit can estimate the child's emotions and adjust the recording frequency based on the estimated emotions. For example, if the child is excited, the recording unit increases the recording frequency to collect more detailed data. For example, if the child is relaxed, the recording unit decreases the recording frequency to collect only the minimum necessary data. For example, if the child is anxious, the recording unit adjusts the recording frequency appropriately to reduce stress. This allows for the collection of detailed data by adjusting the recording frequency according to the child's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. The generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the recording unit may be performed using AI, or not using AI. For example, the recording unit can input the child's emotion data into the generative AI, which can then estimate the emotions and adjust the recording frequency.

[0073] The recording unit can simultaneously acquire biometric information such as the child's body temperature and heart rate during recording. For example, the recording unit can use a sensor linked to a camera to record the child's body temperature in real time. For example, the recording unit can monitor the child's heart rate and issue an alert if there is an abnormality. For example, the recording unit can measure the child's respiratory rate and record their health status in detail. This allows for a detailed understanding of the child's health status by simultaneously acquiring biometric information such as body temperature and heart rate. Some or all of the above-described processes in the recording unit may be performed using AI, for example, or without AI. For example, the recording unit can input biometric information acquired by sensors into a generating AI, which can then analyze the health status.

[0074] The recording unit can record ambient sounds and temperature around the child during recording, allowing it to understand changes in the living environment. For example, the recording unit can record ambient sounds and analyze factors that affect the child's sleep patterns. For example, the recording unit can record room temperature and collect data for appropriate temperature control. For example, the recording unit can record lighting brightness and provide an environment suitable for the child's activities. In this way, changes in the living environment can be understood by recording ambient sounds and temperature around the child. Some or all of the above processing in the recording unit may be performed using AI, for example, or without AI. For example, the recording unit can input ambient sound and temperature data into a generating AI, which can then analyze changes in the living environment.

[0075] The recording unit can estimate the child's emotions and determine the priority of data to record based on the estimated emotions. For example, if the child is excited, the recording unit will prioritize recording behavioral data. For example, if the child is relaxed, the recording unit will prioritize recording sleep data. For example, if the child is anxious, the recording unit will prioritize recording biometric information such as heart rate and body temperature. This allows important data to be recorded preferentially by determining the priority of data to record according to the child's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the recording unit may be performed using AI, for example, or without AI. For example, the recording unit can input the child's emotion data into a generative AI, which can then estimate the emotions and determine the priority of data to record.

[0076] The recording unit can simultaneously record the parent's voice and facial expressions during recording, allowing for analysis of parent-child interactions. For example, the recording unit can analyze the tone of the parent's voice and record the child's response. For example, the recording unit can capture the parent's facial expressions with a camera and analyze their relationship to the child's emotions. For example, the recording unit can transcribe the content of the parent-child conversation into text and analyze the interaction patterns. In this way, parent-child interactions can be analyzed by recording the parent's voice and facial expressions. Some or all of the above processing in the recording unit may be performed using AI, for example, or without AI. For example, the recording unit can input the parent's voice and facial expression data into a generating AI, which can then analyze the parent-child interaction.

[0077] The recording unit can record a child's play and learning activities during recording, allowing for a detailed understanding of their developmental process. For example, the recording unit can videotape a child playing and analyze their developmental process. For example, the recording unit can record a child's learning activities to track their learning progress. For example, the recording unit can record a child's creative activities to help discover their talents. In this way, by recording a child's play and learning activities, a detailed understanding of their developmental process can be obtained. Some or all of the above-described processes in the recording unit may be performed using AI, for example, or without AI. For example, the recording unit can input play and learning activities into a generating AI, which can then analyze the developmental process.

[0078] The advice unit can estimate the child's emotions and adjust the advice based on the estimated emotions. For example, if the child is excited, the advice unit will provide advice to calm the child down. For example, if the child is relaxed, the advice unit will provide advice to maintain that relaxation. For example, if the child is anxious, the advice unit will provide advice to alleviate that anxiety. By adjusting the advice according to the child's emotions, more appropriate advice can be provided. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. The generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the advice unit may be performed using a generative AI, or not using a generative AI. For example, the advice unit can input the child's emotion data into a generative AI, which will estimate the emotion and adjust the advice.

[0079] The advice unit can select the most appropriate advice by referring to past advice history when providing advice. For example, the advice unit may prioritize providing advice that has been effective in the past. For example, the advice unit may analyze past advice history and select highly effective advice. For example, the advice unit may provide advice tailored to the child's development based on past advice history. In this way, the advice unit can provide the most appropriate advice by referring to past advice history. Some or all of the above processes in the advice unit may be performed using, for example, a generative AI, or without a generative AI. For example, the advice unit may input past advice history into a generative AI, which can then select the most appropriate advice.

[0080] The advice unit can apply different advice algorithms depending on the child's developmental stage when providing advice. For example, the advice unit provides advice on sleep and breastfeeding during the neonatal period. For example, the advice unit provides advice on play and learning during the toddler period. For example, the advice unit provides advice on school life and peer relationships during the school-age period. By applying different advice algorithms according to the child's developmental stage, appropriate advice can be provided according to their growth. Some or all of the above processing in the advice unit may be performed using, for example, a generative AI, or without a generative AI. For example, the advice unit can input child developmental stage data into a generative AI, and the generative AI can apply an advice algorithm appropriate to the developmental stage.

[0081] The advice unit can estimate the child's emotions and determine the priority of advice based on the estimated emotions. For example, if the child is excited, the advice unit will prioritize calming advice. For example, if the child is relaxed, the advice unit will prioritize advice to maintain relaxation. For example, if the child is anxious, the advice unit will prioritize advice to reduce anxiety. In this way, important advice can be prioritized by determining the priority of advice according to the child's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the advice unit may be performed using a generative AI, or not using a generative AI. For example, the advice unit can input the child's emotion data into a generative AI, which can estimate the emotions and determine the priority of advice.

[0082] The advice unit can adjust the way it expresses advice, taking into account the parent's stress level, when providing advice. For example, if the parent is stressed, the advice unit will provide concise and easy-to-understand advice. For example, if the parent is relaxed, the advice unit will provide detailed advice. For example, if the parent is tired, the advice unit will provide advice that includes words of encouragement. In this way, by adjusting the way the advice is expressed, taking into account the parent's stress level, the advice unit can provide advice that is easy for the parent to understand. Some or all of the above processing in the advice unit may be performed using, for example, a generative AI, or not using a generative AI. For example, the advice unit can input the parent's stress level data into a generative AI, and the generative AI can adjust the way the advice is expressed according to the stress level.

[0083] The advice unit can adjust the timing of advice based on the child's daily rhythm when providing advice. For example, the advice unit can provide advice to help the child relax before going to sleep. For example, the advice unit can provide advice to help the child become active after waking up. For example, the advice unit can provide advice to stimulate the child's appetite before meals. By adjusting the timing of advice based on the child's daily rhythm, advice can be provided at the appropriate time. Some or all of the above processing in the advice unit may be performed using, for example, a generative AI, or without a generative AI. For example, the advice unit can input the child's daily rhythm data into a generative AI, which can then adjust the timing of advice based on the daily rhythm.

[0084] The communication unit can estimate a child's emotions and determine the urgency of communication based on the estimated emotions. For example, if a child is crying intensely, the communication unit will make a highly urgent call. For example, if a child is crying lightly, the communication unit will make a less urgent call. For example, if a child is feeling anxious, the communication unit will make a moderately urgent call. This allows for a quick response by determining the urgency of communication based on the child's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the communication unit may be performed using a generative AI, or not using a generative AI. For example, the communication unit can input child emotion data into a generative AI, which can estimate the emotion and determine the urgency of communication.

[0085] The liaison unit can record the child's health status in detail when contacting a medical institution, thereby enriching the information provided. For example, the liaison unit can record the child's body temperature and heart rate and provide it to the medical institution. For example, the liaison unit can record the child's symptoms in detail and provide it to the medical institution. For example, the liaison unit can refer to the child's past health history and provide it to the medical institution. This allows for appropriate medical care by recording the child's health status in detail and enriching the information provided to the medical institution. Some or all of the above processes in the liaison unit may be performed using AI, for example, or not using AI. For example, the liaison unit can input health status data into a generating AI, which can then analyze the data and generate information to provide to the medical institution.

[0086] The communication unit can select a communication method when contacting a parent, taking into account the parent's current situation (e.g., whether they are at work). For example, if the parent is at work, the communication unit will contact them via email or message. If the parent is at home, the communication unit will contact them by phone. If the parent is out, the communication unit will contact them via app notification. By selecting a communication method that takes the parent's current situation into account, the communication unit can provide the parent with the most suitable means of communication. Some or all of the above processing in the communication unit may be performed using AI, for example, or not. For example, the communication unit can input data on the parent's current situation into a generating AI, which can then select the most suitable communication method according to the situation.

[0087] The communication unit can estimate the child's emotions and adjust the content of the communication based on the estimated emotions. For example, if the child is crying intensely, the communication unit will send a message with detailed information. For example, if the child is crying lightly, the communication unit will send a message with concise information. For example, if the child is feeling anxious, the communication unit will send a message with reassuring information. In this way, appropriate information can be provided by adjusting the content of the communication based on the child's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the communication unit may be performed using a generative AI, or not using a generative AI. For example, the communication unit can input the child's emotion data into a generative AI, which can estimate the emotion and adjust the content of the communication.

[0088] The liaison department can select the most suitable contact when making a contact by referring to the medical institution's past response history. For example, the liaison department may prioritize selecting medical institutions that have been handled in the past. For example, the liaison department may analyze past response history and select the most suitable medical institution. For example, the liaison department may select a specialist based on past response history. In this way, the most suitable contact can be selected by referring to the medical institution's past response history. Some or all of the above processes in the liaison department may be performed using AI, for example, or not using AI. For example, the liaison department may input past response history data of medical institutions into a generating AI, and the generating AI can select the most suitable contact.

[0089] The liaison unit can transmit data about the child's health status to medical institutions in real time when contact is made. For example, the liaison unit can transmit the child's body temperature and heart rate in real time. For example, the liaison unit can transmit the child's symptoms in real time. For example, the liaison unit can transmit the child's past health history in real time. This enables a rapid medical response by transmitting data about the child's health status in real time. Some or all of the above processing in the liaison unit may be performed using AI, for example, or not using AI. For example, the liaison unit can input health status data into a generating AI, the generating AI can analyze the data, and transmit it to medical institutions in real time.

[0090] The storage unit can estimate a child's emotions and select data to save based on the estimated emotions. For example, the storage unit might prioritize saving moments when the child is laughing. For example, it might prioritize saving moments when the child is crying. For example, it might prioritize saving moments when the child is playing. This allows important moments to be saved preferentially by selecting data based on the child's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. The generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the storage unit may be performed using a generative AI, or not using a generative AI. For example, the storage unit can input child emotion data into a generative AI, which can estimate emotions and select data to save.

[0091] The storage unit can determine the priority of saving data based on its importance. For example, the storage unit might prioritize saving data for important events (such as birthdays). For example, it might save everyday data at an appropriate rate. For example, the storage unit might automatically delete unnecessary data. This allows important data to be saved preferentially by determining the priority of saving based on its importance. Some or all of the above processes in the storage unit may be performed using AI, for example, or without AI. For example, the storage unit can input the importance of the data into a generating AI, which can then determine the priority of saving.

[0092] The storage unit can record the editing history of the data when it is saved, allowing users to review the edits later. For example, the storage unit can record the editing history of the data with a timestamp. For example, the storage unit can record the edits in detail so that they can be reviewed later. For example, the storage unit can make the editing history searchable so that specific edits can be quickly reviewed. This allows users to review the edits later by recording the editing history of the data. Some or all of the above processes in the storage unit may be performed using AI, for example, or without AI. For example, the storage unit can input the editing history data into a generating AI, which can then record and review the edits.

[0093] The storage unit can estimate a child's emotions and adjust how the stored data is displayed based on the estimated emotions. For example, the storage unit might prominently display moments when a child is laughing. For example, it might make moments when a child is crying less noticeable. For example, it might display moments when a child is playing with a fun design. In this way, important moments can be highlighted by adjusting how the stored data is displayed based on the child's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. The generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the storage unit may be performed using a generative AI, or not using a generative AI. For example, the storage unit can input child emotion data into a generative AI, which can then estimate the emotions and adjust how the stored data is displayed.

[0094] The storage unit can ensure data security by automatically backing up data during storage. For example, the storage unit can periodically save data backups to the cloud. For example, the storage unit can ensure data security by saving data backups in multiple locations. For example, the storage unit can enhance security by encrypting and saving data backups. This ensures data security by automatically backing up data. Some or all of the above processes in the storage unit may be performed using AI, for example, or without AI. For example, the storage unit can input backup data into a generating AI, which can then manage the backups.

[0095] The storage unit can save data to the cloud and make it accessible from multiple devices. For example, the storage unit can save data to the cloud and make it accessible from smartphones and tablets. For example, the storage unit can save data to the cloud and make it accessible to all family members. For example, the storage unit can save data to the cloud and make it accessible even when away from home. This makes the data accessible from multiple devices by saving it to the cloud. Some or all of the above processing in the storage unit may be performed using AI, for example, or not using AI. For example, the storage unit can input cloud data into a generating AI, and the generating AI can manage the data.

[0096] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0097] The childcare support system can also include a learning section that provides learning content tailored to the child's developmental stage. The learning section, for example, selects and provides appropriate learning content according to the child's age and developmental stage. For instance, during early childhood, the learning section might provide games to promote the recognition of colors and shapes. For instance, during elementary school, the learning section might provide materials for learning the basics of arithmetic and reading and writing. The learning section could also create and provide individualized learning plans based on the child's interests and concerns. This allows for support of the child's intellectual development by providing learning content appropriate to their developmental stage.

[0098] The childcare support system can also include a stress management unit that monitors parents' stress levels and provides advice to reduce stress. The stress management unit could, for example, monitor parents' heart rate and sleep patterns to assess their stress levels. If a parent is feeling stressed, the stress management unit could suggest breathing exercises or simple exercises to help them relax. If a parent is tired, the stress management unit could advise on when to take a rest. If a parent is relaxed, the stress management unit could suggest lifestyle improvements to prevent stress. This allows for monitoring parents' stress levels and providing appropriate advice, thereby improving parental health and the quality of childcare.

[0099] Childcare support systems can also include a social interaction section to foster children's social skills. This section could, for example, provide event information to offer children opportunities to play with other children. It could also provide community features to promote interaction among parents. Furthermore, it could suggest group activities and workshops to cultivate children's social skills. Finally, it could offer online games and activities for children to play cooperatively with other children. This provides opportunities to foster children's social skills and supports their development.

[0100] The childcare support system may also include a music provider that estimates the child's emotions and plays appropriate music based on those emotions. For example, if the child is excited, the music provider might play calming music to help them relax. If the child is relaxed, the music provider might play soothing music to maintain that state. If the child is feeling anxious, the music provider might play reassuring music to alleviate that anxiety. If the child is playing, the music provider might play cheerful music to enhance their mood. By providing appropriate music according to the child's emotions, the system can help stabilize the child's emotional state.

[0101] The childcare support system could also include an education department that provides educational content to improve parents' childcare skills. For example, the education department could provide the latest research and information on childcare. For example, it could provide videos and articles explaining childcare methods appropriate to a child's developmental stage. For example, it could provide Q&A sessions to help parents resolve their questions and concerns about childcare. For example, it could offer online courses and workshops on childcare. This would allow parents to approach childcare with greater confidence by providing educational content to improve their childcare skills.

[0102] The childcare support system may also include a picture book dispensing unit that estimates the child's emotions and selects an appropriate picture book based on those emotions. For example, if the child is excited, the picture book dispensing unit may provide a picture book with a calming story to soothe them. If the child is relaxed, the picture book dispensing unit may provide a picture book with a pleasant story to maintain that state. If the child is feeling anxious, the picture book dispensing unit may provide a picture book with a reassuring story to alleviate their anxiety. If the child is playing, the picture book dispensing unit may provide a picture book with a cheerful story to enhance their mood. In this way, by providing appropriate picture books according to the child's emotions, the child's emotional state can be stabilized.

[0103] Childcare support systems can also include a sharing section for parents to share their childcare experiences. This sharing section could, for example, provide a platform for parents to share their successes and failures with other parents. It could also allow parents to post advice and tips on childcare, ask questions about childcare and receive answers from other parents, or share photos and videos related to childcare and interact with other parents. This allows parents to learn from each other and improve the quality of their childcare by sharing their experiences.

[0104] The childcare support system can also include a play suggestion unit that estimates the child's emotions and suggests appropriate play based on those emotions. For example, if the child is excited, the play suggestion unit may suggest active play to help the child release energy. If the child is relaxed, the play suggestion unit may suggest calm play to maintain that state. If the child is feeling anxious, the play suggestion unit may suggest play that provides a sense of security to alleviate that anxiety. If the child is playing, the play suggestion unit may suggest creative play to enhance their enjoyable mood. In this way, by suggesting appropriate play according to the child's emotions, the child's emotional state can be stabilized.

[0105] The childcare support system can also include a resources section that provides resources to deepen parents' knowledge of childcare. For example, the resources section could provide specialized books and articles on childcare. For example, it could provide the latest research findings and news on childcare. For example, it could provide an online library on childcare that parents can freely access. For example, it could provide interviews and lectures by childcare experts. By providing resources to deepen parents' knowledge of childcare, it enables parents to engage in childcare more effectively.

[0106] The childcare support system may also include a meal suggestion unit that estimates the child's emotions and suggests appropriate meals based on those emotions. For example, if the child is excited, the meal suggestion unit may suggest a nutritionally balanced meal to help the child relax. If the child is relaxed, the meal suggestion unit may suggest a healthy meal to maintain that state. If the child is feeling anxious, the meal suggestion unit may suggest a meal that provides a sense of security to alleviate that anxiety. If the child is playing, the meal suggestion unit may suggest a fun meal to replenish their energy. In this way, by suggesting appropriate meals according to the child's emotions, the system can support the child's health and emotional well-being.

[0107] The following briefly describes the processing flow for example form 2.

[0108] Step 1: The recording unit automatically records the child's life. For example, it records the child's life through taking pictures with a camera and collects detailed data based on the camera's resolution and the timing of the shots. Step 2: The advice unit provides advice based on the data recorded by the recording unit. For example, it uses a generative AI to analyze the optimal approach based on the child's personality, behavior, and characteristics, and provides specific advice. Step 3: The liaison unit automatically contacts the hospital based on the advice provided by the advisory unit. For example, if there is a problem with the baby's crying, the unit uses crying patterns and voice analysis technology to detect the abnormality and contacts the hospital. Step 4: The storage unit automatically edits and saves the data recorded by the recording unit. For example, it saves the data in an appropriate format based on editing criteria and saving format, and prioritizes saving important data.

[0109] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0110] Data generation model 58 is a form of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include text generation AI, image generation AI, and multimodal generation AI. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats from audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each of the above parts is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example.Furthermore, processing performed by AI, including generative AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by AI, including generative AI.

[0111] Furthermore, the processing performed by the data processing system 10 described above is carried out by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but it may also be carried out by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. In addition, 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.

[0112] Each of the multiple elements described above, including the recording unit, advice unit, communication unit, and storage unit, is implemented in at least one of the smart device 14 and the data processing unit 12. For example, the recording unit automatically records the child's life using the camera 42 of the smart device 14. The advice unit is implemented in the specific processing unit 290 of the data processing unit 12 and provides advice using generated AI. The communication unit is implemented in the specific processing unit 46A of the smart device 14 and automatically contacts the hospital if there is a problem with the crying. The storage unit is implemented in the specific processing unit 290 of the data processing unit 12 and automatically edits and saves the recorded data. The correspondence between each unit and the device or control unit is not limited to the examples described above and can be changed in various ways.

[0113] [Second Embodiment] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0114] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0115] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0116] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0117] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0118] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0119] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0120] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing by the processor 28. The storage 32 stores the specific processing program 56.

[0121] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0122] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0123] In the smart glasses 214, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. 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 acting as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0124] Furthermore, other devices besides the data processing device 12 may also 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 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0125] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0126] The data generation model 58 is a so-called generative AI. An example of a 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 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0127] 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 performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart glasses 214 or an external device, and the smart glasses 214 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0128] Each of the multiple elements described above, including the recording unit, advice unit, communication unit, and storage unit, is implemented in at least one of the smart glasses 214 and the data processing unit 12. For example, the recording unit automatically records the child's life using the camera 42 of the smart glasses 214. The advice unit is implemented in the specific processing unit 290 of the data processing unit 12 and provides advice using generated AI. The communication unit is implemented in the specific processing unit 46A of the smart glasses 214 and automatically contacts a hospital if there is a problem with the crying. The storage unit is implemented in the specific processing unit 290 of the data processing unit 12 and automatically edits and saves the recorded data. The correspondence between each unit and the device or control unit is not limited to the examples described above and can be changed in various ways.

[0129] [Third Embodiment] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0130] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0131] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0132] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0133] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0134] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0135] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0136] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0137] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0138] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0139] In the headset terminal 314, specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads the specific program 60 from the storage 50 and executes the read specific program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific program 60 executed on the RAM 48. The headset terminal 314 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0140] Furthermore, other devices besides the data processing device 12 may also 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 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0141] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0142] The data generation model 58 is a so-called generative AI. An example of a 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 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0143] 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 performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset terminal 314, but may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset terminal 314. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the headset terminal 314 or an external device, and the headset terminal 314 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0144] Each of the multiple elements described above, including the recording unit, advice unit, communication unit, and storage unit, is implemented in at least one of the headset terminal 314 and the data processing unit 12. For example, the recording unit automatically records the child's life using the camera 42 of the headset terminal 314. The advice unit is implemented in the specific processing unit 290 of the data processing unit 12 and provides advice using generated AI. The communication unit is implemented in the control unit 46A of the headset terminal 314 and automatically contacts the hospital if there is a problem with the crying. The storage unit is implemented in the specific processing unit 290 of the data processing unit 12 and automatically edits and saves the recorded data. The correspondence between each unit and the device or control unit is not limited to the examples described above and can be changed in various ways.

[0145] [Fourth Embodiment] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0146] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0147] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0148] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0149] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0150] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS image sensor or CCD image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0151] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0152] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. The robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0153] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0154] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0155] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0156] In robot 414, specific processing is performed by processor 46. A specific program 60 is stored in storage 50. Processor 46 reads the specific program 60 from storage 50 and executes it on RAM 48. The specific processing is achieved by processor 46 acting as a control unit 46A according to the specific program 60 executed on RAM 48. Robot 414 also has data generation model 58 and emotion identification model 59, similar to those of the robot, and can perform processing similar to that of the specific processing unit 290 using these models.

[0157] Furthermore, other devices besides the data processing device 12 may also 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 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0158] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0159] The data generation model 58 is a so-called generative AI. An example of a 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 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0160] 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 performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the robot 414 or an external device, and the robot 414 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0161] Each of the multiple elements described above, including the recording unit, advice unit, communication unit, and storage unit, is implemented in, for example, at least one of the robot 414 and the data processing unit 12. For example, the recording unit automatically records the child's life using the camera 42 of the robot 414. The advice unit is implemented, for example, by the specific processing unit 290 of the data processing unit 12 and provides advice using generated AI. The communication unit is implemented, for example, by the control unit 46A of the robot 414 and automatically contacts the hospital if there is a problem with the crying. The storage unit is implemented, for example, by the specific processing unit 290 of the data processing unit 12 and automatically edits and saves the recorded data. The correspondence between each unit and the device or control unit is not limited to the examples described above and can be changed in various ways.

[0162] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0163] Figure 9 shows the emotion map 400, in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0164] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0165] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0166] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, and motorcycles, emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated based, for example, on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0167] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0168] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0169] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing method for the specific process may be used, which includes computer 22 and multiple other computers.

[0170] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0171] 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.

[0172] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0173] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0174] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0175] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0176] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0177] Furthermore, although the above-described examples were divided into four embodiments, some or all of these embodiments may be combined. Also, the smart device 14, smart glasses 214, headset terminal 314, and robot 414 are just examples, and they may be combined, or other devices may be used. Also, although the above-described examples were divided into two embodiments, Embodiment 1 and Embodiment 2, these may be combined.

[0178] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and other things that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0179] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0180] (Note 1) A recording unit that automatically records the child's daily life, An advice unit that provides advice based on the data recorded by the recording unit, A communication unit that automatically contacts the hospital based on the advice provided by the aforementioned advice unit, The system includes a storage unit that automatically edits and saves the data recorded by the recording unit. A system characterized by the following features. (Note 2) The aforementioned recording unit is Automatically record children's lives through camera photography. The system described in Appendix 1, characterized by the features described herein. (Note 3) The aforementioned advice section, Using generative AI, we analyze what coping strategies worked for children with similar personalities, behaviors, and characteristics to your own child, and then provide advice by combining this with your own child's data. The system described in Appendix 1, characterized by the features described herein. (Note 4) The aforementioned liaison department, The system automatically contacts the hospital if there is a problem with the baby's crying. The system described in Appendix 1, characterized by the features described herein. (Note 5) The aforementioned storage unit is The recording unit automatically edits and saves the recorded data. The system described in Appendix 1, characterized by the features described herein. (Note 6) The aforementioned recording unit is The system estimates the child's emotions and adjusts the frequency of recordings based on the estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 7) The aforementioned recording unit is During recording, biometric information such as the child's body temperature and heart rate is simultaneously acquired. The system described in Appendix 1, characterized by the features described herein. (Note 8) The aforementioned recording unit is During recording, ambient sounds and temperature around the child are recorded to understand changes in their living environment. The system described in Appendix 1, characterized by the features described herein. (Note 9) The aforementioned recording unit is The system estimates the child's emotions and prioritizes the data to record based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 10) The aforementioned recording unit is During recording, the parents' voices and facial expressions are also recorded to analyze the parent-child interaction. The system described in Appendix 1, characterized by the features described herein. (Note 11) The aforementioned recording unit is During recording, we document the child's play and learning activities to gain a detailed understanding of their developmental process. The system described in Appendix 1, characterized by the features described herein. (Note 12) The aforementioned advice section, The system estimates the child's emotions and adjusts the advice based on those estimates. The system described in Appendix 1, characterized by the features described herein. (Note 13) The aforementioned advice section, When providing advice, we select the most appropriate advice by referring to past advice history. The system described in Appendix 1, characterized by the features described herein. (Note 14) The aforementioned advice section, When providing advice, different advice algorithms are applied depending on the child's developmental stage. The system described in Appendix 1, characterized by the features described herein. (Note 15) The aforementioned advice section, Estimate the child's emotions and prioritize advice based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 16) The aforementioned advice section, When providing advice, we adjust the way the advice is phrased to take into account the parents' stress levels. The system described in Appendix 1, characterized by the features described herein. (Note 17) The aforementioned advice section, When providing advice, adjust the timing of the advice based on the child's daily routine. The system described in Appendix 1, characterized by the features described herein. (Note 18) The aforementioned liaison department, The system estimates the child's emotions and determines the urgency of contact based on those estimates. The system described in Appendix 1, characterized by the features described herein. (Note 19) The aforementioned liaison department, When contacting the medical institution, record the child's health condition in detail and provide comprehensive information. The system described in Appendix 1, characterized by the features described herein. (Note 20) The aforementioned liaison department, When contacting parents, we will select a method of contact that takes their current situation into consideration. The system described in Appendix 1, characterized by the features described herein. (Note 21) The aforementioned liaison department, We estimate the child's emotions and adjust the content of our communication based on those estimates. The system described in Appendix 1, characterized by the features described herein. (Note 22) The aforementioned liaison department, When making contact, refer to the medical institution's past response history to select the most suitable contact person. The system described in Appendix 1, characterized by the features described herein. (Note 23) The aforementioned liaison department, When contacting a medical institution, data on the child's health status will be transmitted in real time. The system described in Appendix 1, characterized by the features described herein. (Note 24) The aforementioned storage unit is The system estimates the child's emotions and selects data to save based on the estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 25) The aforementioned storage unit is When saving data, the saving priority is determined based on the importance of the data. The system described in Appendix 1, characterized by the features described herein. (Note 26) The aforementioned storage unit is When saving, the editing history of the data is recorded so that you can review the edits later. The system described in Appendix 1, characterized by the features described herein. (Note 27) The aforementioned storage unit is The system estimates the child's emotions and adjusts how the saved data is displayed based on the estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 28) The aforementioned storage unit is Data is automatically backed up during saving to ensure data security. The system described in Appendix 1, characterized by the features described herein. (Note 29) The aforementioned storage unit is When saving, the data is stored in the cloud and can be accessed from multiple devices. The system described in Appendix 1, characterized by the features described herein. [Explanation of symbols]

[0181] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots

Claims

1. A recording unit that automatically records the child's daily life, An advice unit that provides advice based on the data recorded by the recording unit, A communication unit that automatically contacts the hospital based on the advice provided by the aforementioned advice unit, The system includes a storage unit that automatically edits and saves the data recorded by the recording unit. A system characterized by the following features.

2. The aforementioned recording unit is Automatically record children's lives through camera photography. The system according to feature 1.

3. The aforementioned advice section, Using generative AI, we analyze what coping strategies worked best for children with similar personalities, behaviors, and characteristics to your own child, and then provide advice by combining this with your own child's data. The system according to feature 1.

4. The aforementioned liaison department, The system automatically contacts the hospital if there is a problem with the baby's crying. The system according to feature 1.

5. The aforementioned storage unit is The data recorded by the aforementioned recording unit is automatically edited and saved. The system according to feature 1.

6. The aforementioned recording unit is The system estimates the child's emotions and adjusts the frequency of recordings based on the estimated emotions. The system according to feature 1.

7. The aforementioned recording unit is During recording, biometric information such as the child's body temperature and heart rate is simultaneously acquired. The system according to feature 1.

8. The aforementioned recording unit is During recording, ambient sounds and temperature around the child are recorded to understand changes in their living environment. The system according to feature 1.

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