System

Abstract

An object of the system according to the embodiment is to unitarily monitor and manage the safety of a baby and the environment of a bedroom.SOLUTION: A system according to an embodiment includes a monitoring unit, a notification unit, a detection unit, a monitoring unit, a control unit, an illuminance monitoring unit, a lighting control unit, and a management unit. The monitoring unit monitors the movement of the baby with a camera. The notification unit notifies the abnormality detected by the monitoring unit. The detector detects breathing of the baby. The notification unit notifies the abnormality detected by the detection unit. The monitoring unit monitors the environment with a temperature and humidity sensor. The control unit controls the environment based on the data obtained by the monitoring unit. The illuminance monitoring unit monitors brightness with an illuminance sensor. The illumination control unit controls the illumination based on the data obtained by the illuminance monitoring unit. The management unit analyzes data from each sensor and manages the state of the baby.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

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

[0004] Conventional technology has had the problem of making it difficult to centrally monitor and manage the baby's safety and the bedroom environment.

[0005] The system according to the embodiment aims to centrally monitor and manage the baby's safety and the bedroom environment. [Means for solving the problem]

[0006] The system according to the embodiment comprises a monitoring unit, a notification unit, a detection unit, a monitoring unit, a control unit, an illuminance monitoring unit, a lighting control unit, and a management unit. The monitoring unit monitors the baby's movements using a camera. The notification unit notifies of any abnormalities detected by the monitoring unit. The detection unit detects the baby's breathing. The notification unit notifies of any abnormalities detected by the detection unit. The monitoring unit monitors the environment using a temperature and humidity sensor. The control unit controls the environment based on data obtained by the monitoring unit. The illuminance monitoring unit monitors brightness using an illuminance sensor. The lighting control unit controls lighting based on data obtained by the illuminance monitoring unit. The management unit analyzes data from each sensor and manages the baby's condition. [Effects of the Invention]

[0007] The system according to the embodiment can monitor and manage the baby's safety and the bedroom environment in a unified manner. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8]FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE INVENTION

[0009] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

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

[0012] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

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

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

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

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

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

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. Camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

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

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

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

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

[0028] (Example 1) A monitoring system according to an embodiment of the present invention comprehensively monitors a baby's safety and the bedroom environment, reducing stress for parents. The monitoring system uses a camera to monitor the baby's movements and detects and notifies parents of emergency situations, such as when the baby is lying face down or the face is covered. A vibration sensor also detects the baby's breathing and immediately notifies parents if an abnormality occurs. A temperature and humidity sensor controls the baby's comfortable environment, and a light sensor controls the lighting to ensure the baby sleeps well. Information obtained from these sensors is managed by a generative AI to monitor the baby's overall condition. For example, the monitoring system monitors the baby's movements in real time and immediately notifies parents if an abnormality occurs. For example, if the baby is lying face down or the face is covered, the camera detects this and sends an alert to the parents. A vibration sensor then detects the baby's breathing and immediately notifies parents if an abnormality occurs. For example, if the baby's breathing becomes irregular or stops, the vibration sensor detects the abnormality and notifies the parents. A temperature and humidity sensor also controls the baby's comfortable environment. For example, if the room temperature is too high, the air conditioner will be turned on, and if the humidity is too low, the humidifier will be turned on. An illuminance sensor controls lighting to help babies get a good night's sleep. For example, it dims the lights at night and keeps them at a moderate brightness during the day. This allows the monitoring system to ensure the baby's safety and reduce stress for the parents. This allows the monitoring system to ensure the baby's safety and reduce stress for the parents. For example, parents can check on the baby's condition via their smartphone even when they are out. This allows the baby's safety to be ensured and reduce stress for the parents.

[0029] The watching system according to the embodiment includes a monitoring unit, a notification unit, a detection unit, a monitoring unit, a control unit, and a management unit. The monitoring unit monitors the baby's movements using a camera. The monitoring unit monitors the baby's movements in real time, for example. The monitoring unit can also detect an abnormality when the baby lies face down or covers its face. The monitoring unit can also record the baby's movements and play the recorded images later. The notification unit notifies the parents of an abnormality detected by the monitoring unit. The notification unit can send an alert to the parents, for example, when the baby lies face down or covers its face. The notification unit can also issue an audio alert when an abnormality occurs. The notification unit can also send a notification to a smartphone when an abnormality occurs. The detection unit detects the baby's breathing using a vibration sensor. The detection unit monitors the baby's breathing in real time, for example. The detection unit can also detect an abnormality when the baby's breathing becomes irregular or stops. The detection unit can also record the baby's breathing and play the recorded images later. The monitoring unit constantly monitors the baby's bedroom environment using temperature and humidity sensors. For example, the monitoring unit monitors the temperature and humidity of the baby's bedroom in real time. The monitoring unit can also detect abnormalities when the temperature and humidity of the baby's bedroom are not appropriate. The monitoring unit can also record the temperature and humidity of the baby's bedroom and play them back later. The control unit controls the environment based on the data obtained by the monitoring unit. For example, the control unit can turn on the air conditioner if the room temperature is too high and turn on the humidifier if the humidity is too low. The control unit can also stop the air conditioner if the room temperature is too low and stop the humidifier if the humidity is too high. The control unit can also simultaneously control the air conditioner and humidifier to maintain appropriate room temperature and humidity. The management unit analyzes data from each sensor and manages the baby's overall condition. For example, the management unit can check whether the baby's breathing is normal and whether the room temperature and humidity are appropriate. The management unit can also monitor changes in the baby's health and environment in real time. The management unit can also record the baby's condition and play them back later.As a result, the monitoring system according to the embodiment can ensure the safety of the baby and reduce stress for the parents.

[0030] The monitoring unit can monitor the baby's movements in real time using a camera. The monitoring unit monitors the baby's movements in real time, for example. The monitoring unit can also detect abnormalities when the baby lies face down or when its face is covered. The monitoring unit can also record the baby's movements and play them back later. In this way, by monitoring the baby's movements in real time, abnormalities can be detected early. Some or all of the above-mentioned processing in the monitoring unit may be performed using, for example, AI, or may be performed without using AI. For example, the monitoring unit can input video data acquired by a camera into a generation AI and have the generation AI analyze the baby's movements.

[0031] The notification unit can send an alert to the parents when the baby lies face down or covers its face. For example, the notification unit can send an alert to the parents when the baby lies face down or covers its face. The notification unit can also issue an audio alert when an abnormality occurs. The notification unit can also send a notification to a smartphone when an abnormality occurs. This allows the parents to be immediately notified of the baby's dangerous situation, enabling a prompt response. Some or all of the above-mentioned processing in the notification unit may be performed using AI, for example, or may be performed without using AI. For example, the notification unit can input abnormality detection data from the monitoring unit to a generation AI and cause the generation AI to generate an alert.

[0032] The detection unit can monitor the baby's breathing using a vibration sensor. For example, the detection unit monitors the baby's breathing in real time. The detection unit can also detect abnormalities when the baby's breathing becomes irregular or stops. The detection unit can also record the baby's breathing and play it back later. In this way, by monitoring the baby's breathing, breathing abnormalities can be detected early. Some or all of the above-mentioned processing in the detection unit may be performed using, for example, AI, or may be performed without using AI. For example, the detection unit can input data acquired by the vibration sensor into the generation AI and cause the generation AI to analyze the breathing.

[0033] The notification unit can notify the parents when the baby's breathing becomes irregular or stops. For example, the notification unit notifies the parents when the baby's breathing becomes irregular or stops. The notification unit can also issue a voice alert when an abnormality occurs. The notification unit can also send a notification to a smartphone when an abnormality occurs. This allows the parents to be immediately notified of the baby's breathing abnormality, enabling a prompt response. Some or all of the above-mentioned processing in the notification unit may be performed using AI, for example, or may be performed without using AI. For example, the notification unit can input abnormality detection data from the detection unit to a generation AI and cause the generation AI to generate an alert.

[0034] The monitoring unit can constantly monitor the environment of the baby's bedroom using a temperature and humidity sensor. The monitoring unit, for example, monitors the temperature and humidity of the baby's bedroom in real time. The monitoring unit can also detect abnormalities when the temperature and humidity of the baby's bedroom are not appropriate. The monitoring unit can also record the temperature and humidity of the baby's bedroom and play them back later. This allows the environment of the baby's bedroom to be constantly monitored, thereby maintaining a comfortable environment. Some or all of the above-mentioned processing in the monitoring unit may be performed using, for example, AI, or may be performed without using AI. For example, the monitoring unit can input data acquired by the temperature and humidity sensor into the generation AI and have the generation AI analyze the environment.

[0035] The control unit can activate the air conditioner when the room temperature exceeds a set temperature, and activate the humidifier when the humidity falls below a set value. For example, the control unit can activate the air conditioner when the room temperature exceeds a set temperature. The control unit can also activate the humidifier when the humidity falls below a set value. The control unit can also stop the air conditioner when the room temperature is too low, and stop the humidifier when the humidity is too high. The control unit can also simultaneously control the air conditioner and humidifier to maintain appropriate room temperature and humidity. This allows for appropriate control of the baby's bedroom environment, providing a comfortable environment. Some or all of the above-mentioned processing in the control unit can be performed, for example, using AI, or can be performed without using AI. For example, the control unit can input data from the monitoring unit into the generation AI and have the generation AI control the air conditioner and humidifier.

[0036] The monitoring unit can monitor the brightness of the bedroom using an illuminance sensor. For example, the monitoring unit monitors the brightness of the baby's bedroom in real time. The monitoring unit can also detect an abnormality when the brightness of the baby's bedroom is inappropriate. The monitoring unit can also record the brightness of the baby's bedroom and play it back later. In this way, by monitoring the brightness of the bedroom, an environment in which the baby can sleep well can be provided. Some or all of the above-mentioned processing in the monitoring unit may be performed using, for example, AI, or may be performed without using AI. For example, the monitoring unit can input data acquired by the illuminance sensor into the generation AI and have the generation AI analyze the brightness.

[0037] The control unit can dim the lights at night and maintain a moderate brightness during the day. For example, the control unit dims the lights at night. The control unit can also maintain a moderate brightness during the day. The control unit can also adjust the brightness of the lights based on the baby's sleep state. This allows the lighting to be appropriately controlled so that the baby can sleep well. Some or all of the above-mentioned processing in the control unit may be performed using AI, for example, or may be performed without using AI. For example, the control unit can input data from the monitoring unit into the generation AI and have the generation AI control the lighting.

[0038] The management unit analyzes data from each sensor and can grasp changes in the baby's health condition and environment in real time. For example, the management unit checks whether the baby's breathing is normal and whether the room temperature and humidity are appropriate. The management unit can also grasp changes in the baby's health condition and environment in real time. The management unit can also record the baby's condition and play it back later. This enables quick response by understanding changes in the baby's health condition and environment in real time. Some or all of the above-mentioned processing in the management unit may be performed using, or without, a generation AI, for example. For example, the management unit can input data from each sensor into the generation AI and have the generation AI analyze the data.

[0039] The monitoring unit learns the baby's movement patterns and can detect abnormal movements early. For example, the monitoring unit detects an abnormality when the baby moves in a way that deviates from normal movements. The monitoring unit can also learn a pattern of specific movements made by the baby at a specific time of day and detect an abnormality when the baby deviates from that pattern. The monitoring unit can also determine whether a specific movement made by the baby repeatedly is abnormal. In this way, abnormal movements can be detected early by learning the baby's movement patterns. Some or all of the above-described processing in the monitoring unit may be performed using, for example, AI, or may be performed without using AI. For example, the monitoring unit can input data on the baby's movements into a generation AI and cause the generation AI to learn the movement patterns.

[0040] The monitoring unit can monitor the baby's body temperature and notify if there is an abnormality. For example, the monitoring unit notifies if the baby's body temperature is too high. The monitoring unit can also notify if the baby's body temperature is too low. The monitoring unit can also notify if there is a sudden change in the baby's body temperature. In this way, by monitoring the baby's body temperature, abnormalities in body temperature can be detected early. Some or all of the above-mentioned processing in the monitoring unit may be performed using AI, for example, or may be performed without using AI. For example, the monitoring unit can input the baby's body temperature data into the generation AI and have the generation AI analyze the body temperature.

[0041] The monitoring unit can monitor the baby's sleep cycle and provide an optimal sleeping environment. For example, the monitoring unit can keep the environment quiet when the baby enters a deep sleep. The monitoring unit can also make the environment a little brighter when the baby enters a light sleep. The monitoring unit can also brighten the environment when the baby wakes up to make it easier for the baby to be active. In this way, by monitoring the baby's sleep cycle, an optimal sleeping environment can be provided. Some or all of the above-mentioned processing in the monitoring unit may be performed using, for example, AI, or may be performed without using AI. For example, the monitoring unit can input the baby's sleep data into the generation AI and have the generation AI analyze the sleep cycle.

[0042] The monitoring unit can monitor sounds around the baby and notify the user if an abnormal sound is detected. For example, the monitoring unit notifies the user that a loud noise is generated around the baby. The monitoring unit can also notify the user that a specific sound (e.g., crying) is generated around the baby. The monitoring unit can also notify the user that a continuous sound is generated around the baby. By monitoring the sounds around the baby, abnormal sounds can be detected early. Some or all of the above-described processing in the monitoring unit may be performed using AI, for example, or may be performed without using AI. For example, the monitoring unit can input sound data around the baby to the generation AI and cause the generation AI to detect abnormal sounds.

[0043] The monitoring unit can monitor changes in the baby's weight and notify the user if an abnormality is detected. For example, the monitoring unit can notify the user that an abnormality has occurred if the baby's weight increases suddenly. The monitoring unit can also notify the user that an abnormality has occurred if the baby's weight decreases suddenly. The monitoring unit can also notify the user that an abnormality has occurred if the baby's weight does not change for a certain period of time. In this way, by monitoring changes in the baby's weight, weight abnormalities can be detected early. Some or all of the above-described processing in the monitoring unit may be performed using AI, for example, or may be performed without using AI. For example, the monitoring unit can input the baby's weight data into the generation AI and have the generation AI analyze the weight.

[0044] The monitoring unit can automatically create a baby's growth record and provide it to the parents. The monitoring unit can, for example, record changes in the baby's weight and height and periodically report them to the parents. The monitoring unit can also record the baby's sleep patterns and provide them to the parents. The monitoring unit can also automatically create a record of the baby's meals and provide them to the parents. In this way, by automatically creating a baby's growth record, it is possible to provide convenient information to the parents. Some or all of the above-mentioned processing in the monitoring unit may be performed using, for example, AI, or may be performed without using AI. For example, the monitoring unit can input the baby's growth data into the generation AI and cause the generation AI to create a growth record.

[0045] The notification unit can customize the notification content and provide a notification method that suits the parents' preferences. For example, the notification unit selects a notification method (e.g., voice, text) preferred by the parents and provides the notification. The notification unit can also select notification content (e.g., detailed information, concise information) preferred by the parents and provide the notification. The notification unit can also select a notification timing (e.g., real-time, periodic) preferred by the parents and provide the notification. This allows for more appropriate notification by providing a notification method that suits the parents' preferences. Some or all of the above-described processing in the notification unit may be performed using, or without, AI. For example, the notification unit can input parents' preference data into a generation AI and have the generation AI customize the notification content.

[0046] The notification unit can analyze the notification history and learn the optimal notification timing. For example, the notification unit can analyze the timing of notifications received by the parents in the past and suggest the optimal notification timing. The notification unit can also analyze the content of notifications received by the parents in the past and suggest the optimal notification content. The notification unit can also analyze the method of notification received by the parents in the past and suggest the optimal notification method. In this way, the optimal notification timing can be learned by analyzing the notification history. Some or all of the above-mentioned processing in the notification unit may be performed using, for example, AI, or may be performed without using AI. For example, the notification unit can input notification history data to a generation AI and cause the generation AI to learn the optimal notification timing.

[0047] The notification unit can report the baby's current condition in detail when notifying. For example, the notification unit can report the baby's body temperature and breathing condition in detail. The notification unit can also report the baby's sleeping condition and movements in detail. The notification unit can also report the baby's surrounding environment (temperature, humidity, illuminance) in detail. This allows parents to accurately understand the situation by reporting the baby's current condition in detail. Some or all of the above-mentioned processing in the notification unit may be performed using AI, for example, or may be performed without using AI. For example, the notification unit can input data from each sensor into the generation AI and have the generation AI execute a detailed report of the baby's condition.

[0048] The notification unit can also provide environmental information about the baby's surroundings when making a notification. For example, the notification unit can notify the temperature and humidity around the baby. The notification unit can also notify the illuminance around the baby. The notification unit can also notify the sound environment around the baby. By providing environmental information about the baby's surroundings, parents can accurately understand the situation. Some or all of the above-mentioned processing in the notification unit can be performed using AI, for example, or without AI. For example, the notification unit can input data from each sensor into the generation AI and cause the generation AI to provide environmental information.

[0049] The notification unit can display a graph of the progress of the baby's health condition at the time of notification. The notification unit can, for example, display a graph of the progress of the baby's body temperature. The notification unit can also display a graph of the progress of the baby's breathing condition. The notification unit can also display a graph of the progress of the baby's sleeping condition. By displaying a graph of the progress of the baby's health condition, parents can visually grasp the situation. Some or all of the above-mentioned processing in the notification unit can be performed, for example, using AI or without using AI. For example, the notification unit can input data from each sensor into the generation AI and cause the generation AI to display a graph of the progress of the health condition.

[0050] The notification unit can provide advice according to the baby's condition at the time of notification. For example, if the baby's body temperature is high, the notification unit can advise cooling methods. The notification unit can also advise consulting a doctor if the baby's breathing is irregular. The notification unit can also advise how to improve the baby's environment if the baby is not sleeping well. This allows parents to take appropriate action by providing advice according to the baby's condition. Some or all of the above-mentioned processing in the notification unit may be performed using, or without, AI. For example, the notification unit can input data from each sensor into a generation AI and cause the generation AI to generate advice.

[0051] The detection unit can detect the baby's heart rate and notify if there is an abnormality. For example, the detection unit can notify if the baby's heart rate is too high. The detection unit can also notify if the baby's heart rate is too low. The detection unit can also notify if there is a sudden change in the baby's heart rate. In this way, by detecting the baby's heart rate, heart rate abnormalities can be detected early. Some or all of the above-mentioned processing in the detection unit may be performed using AI, for example, or may be performed without using AI. For example, the detection unit can input the baby's heart rate data to the generation AI and have the generation AI analyze the heart rate.

[0052] The detection unit can detect the baby's body movements and notify if there is an abnormality. For example, the detection unit can notify as an abnormality if the baby moves in a way that deviates from normal movements. The detection unit can also notify as an abnormality if the baby moves in a way that deviates from a pattern of specific movements during a specific time period. The detection unit can also determine whether a specific movement is abnormal if the baby repeats it. In this way, by detecting the baby's body movements, abnormal movements can be detected early. Some or all of the above-mentioned processing in the detection unit may be performed using, for example, AI, or may be performed without using AI. For example, the detection unit can input the baby's body movement data to the generation AI and have the generation AI analyze the body movements.

[0053] The detection unit can detect the baby's skin color and notify if there is an abnormality. For example, the detection unit can notify if the baby's skin color turns pale. The detection unit can also notify if the baby's skin color turns red. The detection unit can also notify if there is a sudden change in the baby's skin color. In this way, by detecting the baby's skin color, skin abnormalities can be detected early. Some or all of the above-mentioned processing in the detection unit may be performed using AI, for example, or may be performed without using AI. For example, the detection unit can input the baby's skin color data to the generation AI and cause the generation AI to analyze the skin color.

[0054] The detection unit can detect the baby's body temperature and notify if there is an abnormality. For example, the detection unit can notify if the baby's body temperature is too high. The detection unit can also notify if the baby's body temperature is too low. The detection unit can also notify if there is a sudden change in the baby's body temperature. In this way, by detecting the baby's body temperature, abnormalities in body temperature can be detected early. Some or all of the above-mentioned processing in the detection unit may be performed using AI, for example, or may be performed without using AI. For example, the detection unit can input the baby's body temperature data into the generation AI and have the generation AI analyze the body temperature.

[0055] The detection unit can detect the baby's sleep state and notify the user if an abnormality is detected. For example, the detection unit can notify the user that an abnormality exists if the baby deviates from a normal sleep pattern. The detection unit can also notify the user that an abnormality exists if the baby does not exhibit a specific sleep pattern during a specific time period. The detection unit can also notify the user that an abnormality exists if the baby makes abnormal movements while sleeping. In this way, by detecting the baby's sleep state, sleep abnormalities can be detected early. Some or all of the above-described processing in the detection unit may be performed using AI, for example, or may be performed without using AI. For example, the detection unit can input the baby's sleep data into the generation AI and have the generation AI analyze the sleep state.

[0056] The detection unit can automatically create a baby's growth record and provide it to the parents. The detection unit can, for example, record changes in the baby's weight and height and periodically report them to the parents. The detection unit can also record the baby's sleep patterns and provide them to the parents. The detection unit can also automatically create a record of the baby's meals and provide them to the parents. In this way, by automatically creating a baby's growth record, it is possible to provide useful information to the parents. Some or all of the above-mentioned processing in the detection unit may be performed using AI, for example, or may be performed without using AI. For example, the detection unit can input the baby's growth data into the generation AI and cause the generation AI to create a growth record.

[0057] The monitoring unit can monitor the sound environment around the baby and notify if there is an abnormality. For example, the monitoring unit notifies if a loud noise occurs around the baby. The monitoring unit can also notify if a specific sound (e.g., crying) occurs around the baby. The monitoring unit can also notify if a continuous sound occurs around the baby. In this way, by monitoring the sound environment around the baby, abnormal sounds can be detected early. Some or all of the above-mentioned processing in the monitoring unit may be performed using AI, for example, or may be performed without using AI. For example, the monitoring unit can input sound data around the baby to the generation AI and cause the generation AI to detect abnormal sounds.

[0058] The monitoring unit can monitor the air quality in the baby's bedroom and notify the user if an abnormality is detected. For example, the monitoring unit can notify the user if the carbon dioxide concentration in the air in the baby's bedroom is too high. The monitoring unit can also notify the user if the formaldehyde concentration in the air in the baby's bedroom is too high. The monitoring unit can also notify the user if the particulate concentration in the air in the baby's bedroom is too high. In this way, by monitoring the air quality in the baby's bedroom, abnormalities in the air quality can be detected early. Some or all of the above-described processing in the monitoring unit may be performed using, or without, AI. For example, the monitoring unit can input air quality data to a generation AI and have the generation AI perform an air quality analysis.

[0059] The monitoring unit can monitor the lighting conditions in the baby's bedroom and provide an optimal lighting environment. For example, the monitoring unit can dim the lights at night to make it easier for the baby to sleep. The monitoring unit can also brighten the lights in the morning to make it easier for the baby to wake up. The monitoring unit can also maintain a moderate brightness during the day to make it easier for the baby to be active. In this way, by monitoring the lighting conditions in the baby's bedroom, an optimal lighting environment can be provided. Some or all of the above-mentioned processing in the monitoring unit may be performed using, for example, AI, or may be performed without using AI. For example, the monitoring unit can input lighting condition data into the generation AI and cause the generation AI to analyze the lighting environment.

[0060] The monitoring unit can monitor temperature changes in the baby's bedroom and notify the user if an abnormality is detected. For example, the monitoring unit can notify the user that an abnormality exists if the temperature in the baby's bedroom is too high. The monitoring unit can also notify the user that an abnormality exists if the temperature in the baby's bedroom is too low. The monitoring unit can also notify the user that an abnormality exists if the temperature in the baby's bedroom changes suddenly. In this way, by monitoring temperature changes in the baby's bedroom, temperature abnormalities can be detected early. Some or all of the above-described processing in the monitoring unit may be performed using AI, for example, or may be performed without using AI. For example, the monitoring unit can input temperature data into the generation AI and have the generation AI analyze the temperature changes.

[0061] The monitoring unit can monitor humidity changes in the baby's bedroom and notify the user if an abnormality is detected. For example, the monitoring unit can notify the user that the humidity in the baby's bedroom is too high. The monitoring unit can also notify the user that the humidity in the baby's bedroom is too low. The monitoring unit can also notify the user that the humidity in the baby's bedroom changes suddenly. In this way, by monitoring humidity changes in the baby's bedroom, humidity abnormalities can be detected early. Some or all of the above-described processing in the monitoring unit can be performed using AI, for example, or can be performed without using AI. For example, the monitoring unit can input humidity data to the generation AI and have the generation AI analyze the humidity changes.

[0062] The control unit can adjust the air conditioner settings based on the baby's body temperature. For example, if the baby's body temperature is too high, the control unit can lower the temperature of the air conditioner. The control unit can also raise the temperature of the air conditioner if the baby's body temperature is too low. The control unit can also adjust the air conditioner settings if the baby's body temperature changes suddenly. In this way, an appropriate temperature environment can be provided by adjusting the air conditioner settings based on the baby's body temperature. Some or all of the above-mentioned processing in the control unit may be performed using AI, for example, or may be performed without using AI. For example, the control unit can input the baby's body temperature data into the generation AI and have the generation AI adjust the air conditioner settings.

[0063] The control unit can adjust the brightness of the lighting based on the baby's sleep state. For example, the control unit dims the lighting at night to make it easier for the baby to sleep. The control unit can also brighten the lighting in the morning to make it easier for the baby to wake up. The control unit can also maintain a moderate brightness during the day to make it easier for the baby to be active. In this way, an optimal sleeping environment can be provided by adjusting the brightness of the lighting based on the baby's sleep state. Some or all of the above-mentioned processing in the control unit may be performed using, for example, AI, or may be performed without using AI. For example, the control unit can input the baby's sleep data into the generation AI and have the generation AI adjust the brightness of the lighting.

[0064] The control unit can adjust the humidifier settings based on the baby's breathing condition. For example, the control unit adjusts the humidifier settings when the baby's breathing is irregular. The control unit can also maintain the humidifier settings when the baby's breathing is normal. The control unit can also change the humidifier settings when the baby's breathing has stopped. In this way, an appropriate humidity environment can be provided by adjusting the humidifier settings based on the baby's breathing condition. Some or all of the above-mentioned processing in the control unit may be performed using AI, for example, or may be performed without using AI. For example, the control unit can input the baby's breathing data into the generation AI and cause the generation AI to adjust the humidifier settings.

[0065] The control unit can control the noise canceling function based on the sound environment around the baby. For example, the control unit can enhance the noise canceling function when a loud noise occurs around the baby. The control unit can also maintain the noise canceling function when a quiet environment is required around the baby. The control unit can also adjust the noise canceling function when continuous noise occurs around the baby. In this way, an appropriate sound environment can be provided by controlling the noise canceling function based on the sound environment around the baby. Some or all of the above-mentioned processing in the control unit can be performed using, for example, AI, or can be performed without using AI. For example, the control unit can input sound environment data to a generation AI and cause the generation AI to control the noise canceling function.

[0066] The control unit can control the air purifier based on the air quality in the baby's bedroom. For example, the control unit can activate the air purifier when the carbon dioxide concentration in the air in the baby's bedroom is too high. The control unit can also activate the air purifier when the formaldehyde concentration in the air in the baby's bedroom is too high. The control unit can also activate the air purifier when the particulate concentration in the air in the baby's bedroom is too high. In this way, an appropriate air environment can be provided by controlling the air purifier based on the air quality in the baby's bedroom. Some or all of the above-mentioned processing in the control unit can be performed, for example, using AI or without AI. For example, the control unit can input air quality data to the generation AI and have the generation AI control the air purifier.

[0067] The control unit can control the opening and closing of curtains based on the lighting conditions in the baby's bedroom. For example, the control unit closes the curtains at night to make it easier for the baby to sleep. The control unit can also open the curtains in the morning to make it easier for the baby to wake up. The control unit can also open the curtains moderately during the day to make it easier for the baby to be active. In this way, an appropriate lighting environment can be provided by controlling the opening and closing of curtains based on the lighting conditions in the baby's bedroom. Some or all of the above-mentioned processing in the control unit may be performed using, for example, AI, or may be performed without using AI. For example, the control unit can input lighting condition data into the generation AI and cause the generation AI to control the opening and closing of curtains.

[0068] The management unit can integrate data from each sensor and comprehensively evaluate the baby's health condition. For example, the management unit can integrate data on the baby's body temperature, breathing, and heart rate to evaluate the health condition. The management unit can also integrate data on the baby's sleep state, body movement, and skin color to evaluate the health condition. The management unit can also integrate environmental data (temperature, humidity, illuminance) around the baby to evaluate the health condition. In this way, by integrating data from each sensor, the baby's health condition can be comprehensively evaluated. Some or all of the above-mentioned processing in the management unit may be performed using, or without, a generation AI. For example, the management unit can input data from each sensor into the generation AI and have the generation AI integrate and evaluate the data.

[0069] The management unit can analyze past data and predict the baby's health condition. For example, the management unit can analyze the baby's past body temperature data and predict future changes in body temperature. The management unit can also analyze the baby's past breathing data and predict future breathing conditions. The management unit can also analyze the baby's past sleep data and predict future sleep patterns. This makes it possible to predict the baby's health condition by analyzing past data. Some or all of the above-mentioned processing in the management unit may be performed using, for example, a generation AI, or may be performed without using a generation AI. For example, the management unit can input past data into the generation AI and have the generation AI execute a health condition prediction.

[0070] The management unit can provide advice to parents based on the baby's health condition. For example, if the baby's body temperature is high, the management unit can advise how to cool the baby. The management unit can also advise the parents to consult a doctor if the baby's breathing is irregular. The management unit can also advise how to improve the baby's environment if the baby is not sleeping well. In this way, by providing advice based on the baby's health condition, parents can take appropriate action. Some or all of the above-mentioned processing in the management unit may be performed using, or without, a generation AI. For example, the management unit can input health condition data into the generation AI and cause the generation AI to generate advice.

[0071] The management unit can integrate data from each sensor and automatically create a baby's growth record. The management unit, for example, records changes in the baby's weight and height and periodically reports them to the parents. The management unit can also record the baby's sleep patterns and provide them to the parents. The management unit can also automatically create a record of the baby's meals and provide them to the parents. In this way, by integrating data from each sensor, a baby's growth record can be automatically created. Some or all of the above-mentioned processing in the management unit may be performed using, or without, a generation AI. For example, the management unit can input data from each sensor into the generation AI and have the generation AI create a growth record.

[0072] The management unit analyzes data from each sensor and can detect abnormalities in the baby's health at an early stage. For example, the management unit analyzes the baby's body temperature data and can detect abnormalities at an early stage. The management unit can also analyze the baby's breathing data and can detect abnormalities at an early stage. The management unit can also analyze the baby's sleep data and can detect abnormalities at an early stage. In this way, by analyzing the data from each sensor, abnormalities in the baby's health can be detected at an early stage. Some or all of the above-mentioned processing in the management unit may be performed using, for example, a generation AI, or may be performed without using a generation AI. For example, the management unit can input data from each sensor into the generation AI and have the generation AI detect abnormalities.

[0073] The management unit can create a health status report of the baby based on data from each sensor and provide it to the parents. The management unit can create a health status report based on data on the baby's body temperature, breathing, and heart rate, for example. The management unit can also create a health status report based on data on the baby's sleep state, body movement, and skin color. The management unit can also create a health status report based on environmental data (temperature, humidity, illuminance) around the baby. In this way, by creating a health status report based on data from each sensor, parents can accurately understand the baby's health status. Some or all of the above-mentioned processing in the management unit may be performed using, or without, a generation AI, for example. For example, the management unit can input data from each sensor into the generation AI and cause the generation AI to create a health status report.

[0074] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0075] The monitoring unit can monitor the baby's body temperature and notify the user if there is an abnormality. For example, if the baby's body temperature is too high, it notifies the user that there is an abnormality. The monitoring unit can also notify the user that there is an abnormality if the baby's body temperature is too low. The monitoring unit can also notify the user that there is an abnormality if there is a sudden change in the baby's body temperature. In this way, by monitoring the baby's body temperature, abnormalities in body temperature can be detected early. Some or all of the above-mentioned processing in the monitoring unit may be performed using AI, for example, or may be performed without using AI. For example, the monitoring unit can input the baby's body temperature data into the generation AI and have the generation AI analyze the body temperature.

[0076] The detection unit can detect the baby's heart rate and notify the user if an abnormality is detected. For example, if the baby's heart rate is too high, the detection unit can notify the user that an abnormality exists. The detection unit can also notify the user that an abnormality exists if the baby's heart rate is too low. The detection unit can also notify the user that an abnormality exists if the baby's heart rate changes suddenly. In this way, by detecting the baby's heart rate, abnormalities in the heart rate can be detected early. Some or all of the above-described processing in the detection unit may be performed using AI, for example, or may be performed without using AI. For example, the detection unit can input the baby's heart rate data to the generation AI and have the generation AI analyze the heart rate.

[0077] The management unit can integrate data from each sensor and comprehensively evaluate the baby's health condition. For example, it can integrate data on the baby's body temperature, breathing, and heart rate to evaluate the health condition. The management unit can also integrate data on the baby's sleep state, body movement, and skin color to evaluate the health condition. The management unit can also integrate environmental data (temperature, humidity, illuminance) around the baby to evaluate the health condition. In this way, by integrating data from each sensor, the baby's health condition can be comprehensively evaluated. Some or all of the above-mentioned processing in the management unit may be performed using, or without, a generation AI. For example, the management unit can input data from each sensor into the generation AI and have the generation AI integrate and evaluate the data.

[0078] The notification unit can customize the notification content and provide a notification method that suits the parents' preferences. For example, the notification unit selects the notification method (e.g., voice, text) preferred by the parents and provides the notification. The notification unit can also select the notification content (e.g., detailed information, concise information) preferred by the parents and provide the notification. The notification unit can also select the notification timing (e.g., real-time, periodic) preferred by the parents and provide the notification. This allows for more appropriate notification by providing a notification method that suits the parents' preferences. Some or all of the above-described processing in the notification unit may be performed using AI, for example, or may be performed without using AI. For example, the notification unit can input the parents' preference data into the generation AI and have the generation AI customize the notification content.

[0079] The detection unit can monitor changes in the baby's weight and notify if there is an abnormality. For example, if the baby's weight increases suddenly, it notifies as an abnormality. The detection unit can also notify as an abnormality if the baby's weight decreases suddenly. The detection unit can also notify as an abnormality if the baby's weight does not change for a certain period of time. In this way, by monitoring changes in the baby's weight, weight abnormalities can be detected early. Some or all of the above-mentioned processing in the detection unit may be performed using AI, for example, or may be performed without using AI. For example, the detection unit can input the baby's weight data into the generation AI and have the generation AI perform weight analysis.

[0080] The monitoring unit can monitor the air quality in the baby's bedroom and notify the user if an abnormality is detected. For example, if the carbon dioxide concentration in the air in the baby's bedroom is too high, the monitoring unit can notify the user as an abnormality. The monitoring unit can also notify the user as an abnormality if the formaldehyde concentration in the air in the baby's bedroom is too high. The monitoring unit can also notify the user as an abnormality if the particulate concentration in the air in the baby's bedroom is too high. In this way, by monitoring the air quality in the baby's bedroom, abnormalities in the air quality can be detected early. Some or all of the above-described processing in the monitoring unit may be performed using, or without, AI. For example, the monitoring unit can input air quality data to the generation AI and have the generation AI perform an air quality analysis.

[0081] The management unit can analyze past data and predict the baby's health condition. For example, it can analyze the baby's past body temperature data and predict future changes in body temperature. The management unit can also analyze the baby's past breathing data and predict future breathing conditions. The management unit can also analyze the baby's past sleep data and predict future sleep patterns. This makes it possible to predict the baby's health condition by analyzing past data. Some or all of the above-mentioned processing in the management unit may be performed using, for example, a generation AI, or may be performed without using a generation AI. For example, the management unit can input past data into the generation AI and have the generation AI perform a health condition prediction.

[0082] The processing flow of the first embodiment will be briefly explained below.

[0083] Step 1: The monitoring unit monitors the baby's movements using a camera. For example, it can monitor the baby's movements in real time and detect abnormalities such as when the baby lies face down or when the face is covered. It can also record the baby's movements and play them back later. Step 2: The notification unit notifies the parents of any abnormalities detected by the monitoring unit. For example, if the baby lies face down or covers its face, the notification unit will send an alert to the parents. It can also issue a voice alert or send a notification to a smartphone if an abnormality occurs. Step 3: The detector detects the baby's breathing using a vibration sensor. For example, it can monitor the baby's breathing in real time and detect abnormalities if it becomes irregular or stops. It can also record the baby's breathing and play it back later. Step 4: The monitoring unit constantly monitors the baby's bedroom environment using temperature and humidity sensors. For example, it monitors the temperature and humidity in the bedroom in real time and detects abnormalities if they are not appropriate. It can also record the temperature and humidity and play them back later. Step 5: The control unit controls the environment based on the data obtained by the monitoring unit. For example, it turns on the air conditioner if the room temperature is too high, and turns on the humidifier if the humidity is too low. It can also stop the air conditioner if the room temperature is too low, and stop the humidifier if the humidity is too high. It can also control the air conditioner and humidifier simultaneously to maintain appropriate room temperature and humidity. Step 6: The illuminance monitoring unit monitors the brightness using an illuminance sensor. For example, it can monitor the brightness of a baby's bedroom in real time and detect an abnormality if it is not appropriate. It can also record the brightness and play it back later. Step 7: The lighting control unit controls the lighting based on the data obtained by the illuminance monitoring unit. For example, if the brightness is not appropriate, the lighting can be adjusted. Step 8: The management unit analyzes the data from each sensor and manages the baby's overall condition. For example, it checks whether the baby is breathing normally and whether the room temperature and humidity are appropriate. It can also monitor changes in the baby's health and environment in real time, record them, and play them back later.

[0084] (Example 2) A monitoring system according to an embodiment of the present invention comprehensively monitors a baby's safety and the bedroom environment, reducing stress for parents. The monitoring system uses a camera to monitor the baby's movements and detects and notifies parents of emergency situations, such as when the baby is lying face down or the face is covered. A vibration sensor also detects the baby's breathing and immediately notifies parents if an abnormality occurs. A temperature and humidity sensor controls the baby's comfortable environment, and a light sensor controls the lighting to ensure the baby sleeps well. Information obtained from these sensors is managed by a generative AI to monitor the baby's overall condition. For example, the monitoring system monitors the baby's movements in real time and immediately notifies parents if an abnormality occurs. For example, if the baby is lying face down or the face is covered, the camera detects this and sends an alert to the parents. A vibration sensor then detects the baby's breathing and immediately notifies parents if an abnormality occurs. For example, if the baby's breathing becomes irregular or stops, the vibration sensor detects the abnormality and notifies the parents. A temperature and humidity sensor also controls the baby's comfortable environment. For example, if the room temperature is too high, the air conditioner will be turned on, and if the humidity is too low, the humidifier will be turned on. An illuminance sensor controls lighting to help babies get a good night's sleep. For example, it dims the lights at night and keeps them at a moderate brightness during the day. This allows the monitoring system to ensure the baby's safety and reduce stress for the parents. This allows the monitoring system to ensure the baby's safety and reduce stress for the parents. For example, parents can check on the baby's condition via their smartphone even when they are out. This allows the baby's safety to be ensured and reduce stress for the parents.

[0085] The watching system according to the embodiment includes a monitoring unit, a notification unit, a detection unit, a monitoring unit, a control unit, and a management unit. The monitoring unit monitors the baby's movements using a camera. The monitoring unit monitors the baby's movements in real time, for example. The monitoring unit can also detect an abnormality when the baby lies face down or covers its face. The monitoring unit can also record the baby's movements and play the recorded images later. The notification unit notifies the parents of an abnormality detected by the monitoring unit. The notification unit can send an alert to the parents, for example, when the baby lies face down or covers its face. The notification unit can also issue an audio alert when an abnormality occurs. The notification unit can also send a notification to a smartphone when an abnormality occurs. The detection unit detects the baby's breathing using a vibration sensor. The detection unit monitors the baby's breathing in real time, for example. The detection unit can also detect an abnormality when the baby's breathing becomes irregular or stops. The detection unit can also record the baby's breathing and play the recorded images later. The monitoring unit constantly monitors the baby's bedroom environment using temperature and humidity sensors. For example, the monitoring unit monitors the temperature and humidity of the baby's bedroom in real time. The monitoring unit can also detect abnormalities when the temperature and humidity of the baby's bedroom are not appropriate. The monitoring unit can also record the temperature and humidity of the baby's bedroom and play them back later. The control unit controls the environment based on the data obtained by the monitoring unit. For example, the control unit can turn on the air conditioner if the room temperature is too high and turn on the humidifier if the humidity is too low. The control unit can also stop the air conditioner if the room temperature is too low and stop the humidifier if the humidity is too high. The control unit can also simultaneously control the air conditioner and humidifier to maintain appropriate room temperature and humidity. The management unit analyzes data from each sensor and manages the baby's overall condition. For example, the management unit can check whether the baby's breathing is normal and whether the room temperature and humidity are appropriate. The management unit can also monitor changes in the baby's health and environment in real time. The management unit can also record the baby's condition and play them back later.As a result, the monitoring system according to the embodiment can ensure the safety of the baby and reduce stress for the parents.

[0086] The monitoring unit can monitor the baby's movements in real time using a camera. The monitoring unit monitors the baby's movements in real time, for example. The monitoring unit can also detect abnormalities when the baby lies face down or when its face is covered. The monitoring unit can also record the baby's movements and play them back later. In this way, by monitoring the baby's movements in real time, abnormalities can be detected early. Some or all of the above-mentioned processing in the monitoring unit may be performed using, for example, AI, or may be performed without using AI. For example, the monitoring unit can input video data acquired by a camera into a generation AI and have the generation AI analyze the baby's movements.

[0087] The notification unit can send an alert to the parents when the baby lies face down or covers its face. For example, the notification unit can send an alert to the parents when the baby lies face down or covers its face. The notification unit can also issue an audio alert when an abnormality occurs. The notification unit can also send a notification to a smartphone when an abnormality occurs. This allows the parents to be immediately notified of the baby's dangerous situation, enabling a prompt response. Some or all of the above-mentioned processing in the notification unit may be performed using AI, for example, or may be performed without using AI. For example, the notification unit can input abnormality detection data from the monitoring unit to a generation AI and cause the generation AI to generate an alert.

[0088] The detection unit can monitor the baby's breathing using a vibration sensor. For example, the detection unit monitors the baby's breathing in real time. The detection unit can also detect abnormalities when the baby's breathing becomes irregular or stops. The detection unit can also record the baby's breathing and play it back later. In this way, by monitoring the baby's breathing, breathing abnormalities can be detected early. Some or all of the above-mentioned processing in the detection unit may be performed using, for example, AI, or may be performed without using AI. For example, the detection unit can input data acquired by the vibration sensor into the generation AI and cause the generation AI to analyze the breathing.

[0089] The notification unit can notify the parents when the baby's breathing becomes irregular or stops. For example, the notification unit notifies the parents when the baby's breathing becomes irregular or stops. The notification unit can also issue a voice alert when an abnormality occurs. The notification unit can also send a notification to a smartphone when an abnormality occurs. This allows the parents to be immediately notified of the baby's breathing abnormality, enabling a prompt response. Some or all of the above-mentioned processing in the notification unit may be performed using AI, for example, or may be performed without using AI. For example, the notification unit can input abnormality detection data from the detection unit to a generation AI and cause the generation AI to generate an alert.

[0090] The monitoring unit can constantly monitor the environment of the baby's bedroom using a temperature and humidity sensor. The monitoring unit, for example, monitors the temperature and humidity of the baby's bedroom in real time. The monitoring unit can also detect abnormalities when the temperature and humidity of the baby's bedroom are not appropriate. The monitoring unit can also record the temperature and humidity of the baby's bedroom and play them back later. This allows the environment of the baby's bedroom to be constantly monitored, thereby maintaining a comfortable environment. Some or all of the above-mentioned processing in the monitoring unit may be performed using, for example, AI, or may be performed without using AI. For example, the monitoring unit can input data acquired by the temperature and humidity sensor into the generation AI and have the generation AI analyze the environment.

[0091] The control unit can activate the air conditioner when the room temperature exceeds a set temperature, and activate the humidifier when the humidity falls below a set value. For example, the control unit can activate the air conditioner when the room temperature exceeds a set temperature. The control unit can also activate the humidifier when the humidity falls below a set value. The control unit can also stop the air conditioner when the room temperature is too low, and stop the humidifier when the humidity is too high. The control unit can also simultaneously control the air conditioner and humidifier to maintain appropriate room temperature and humidity. This allows for appropriate control of the baby's bedroom environment, providing a comfortable environment. Some or all of the above-mentioned processing in the control unit can be performed, for example, using AI, or can be performed without using AI. For example, the control unit can input data from the monitoring unit into the generation AI and have the generation AI control the air conditioner and humidifier.

[0092] The monitoring unit can monitor the brightness of the bedroom using an illuminance sensor. For example, the monitoring unit monitors the brightness of the baby's bedroom in real time. The monitoring unit can also detect an abnormality when the brightness of the baby's bedroom is inappropriate. The monitoring unit can also record the brightness of the baby's bedroom and play it back later. In this way, by monitoring the brightness of the bedroom, an environment in which the baby can sleep well can be provided. Some or all of the above-mentioned processing in the monitoring unit may be performed using, for example, AI, or may be performed without using AI. For example, the monitoring unit can input data acquired by the illuminance sensor into the generation AI and have the generation AI analyze the brightness.

[0093] The control unit can dim the lights at night and maintain a moderate brightness during the day. For example, the control unit dims the lights at night. The control unit can also maintain a moderate brightness during the day. The control unit can also adjust the brightness of the lights based on the baby's sleep state. This allows the lighting to be appropriately controlled so that the baby can sleep well. Some or all of the above-mentioned processing in the control unit may be performed using AI, for example, or may be performed without using AI. For example, the control unit can input data from the monitoring unit into the generation AI and have the generation AI control the lighting.

[0094] The management unit analyzes data from each sensor and can grasp changes in the baby's health condition and environment in real time. For example, the management unit checks whether the baby's breathing is normal and whether the room temperature and humidity are appropriate. The management unit can also grasp changes in the baby's health condition and environment in real time. The management unit can also record the baby's condition and play it back later. This enables quick response by understanding changes in the baby's health condition and environment in real time. Some or all of the above-mentioned processing in the management unit may be performed using, or without, a generation AI, for example. For example, the management unit can input data from each sensor into the generation AI and have the generation AI analyze the data.

[0095] The monitoring unit can estimate the baby's emotions and adjust the monitoring frequency based on the estimated baby's emotions. For example, the monitoring unit can increase the monitoring frequency when the baby is feeling anxious. The monitoring unit can also decrease the monitoring frequency when the baby is relaxed. The monitoring unit can also maintain a medium monitoring frequency when the baby is excited. This allows for more appropriate monitoring by adjusting the monitoring frequency according to the baby's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or a generation AI. The generation AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-mentioned processing in the monitoring unit can be performed using AI, for example, or without AI. For example, the monitoring unit can input the baby's facial expression data into the generation AI and cause the generation AI to estimate the emotion.

[0096] The monitoring unit learns the baby's movement patterns and can detect abnormal movements early. For example, the monitoring unit detects an abnormality when the baby moves in a way that deviates from normal movements. The monitoring unit can also learn a pattern of specific movements made by the baby at a specific time of day and detect an abnormality when the baby deviates from that pattern. The monitoring unit can also determine whether a specific movement made by the baby repeatedly is abnormal. In this way, abnormal movements can be detected early by learning the baby's movement patterns. Some or all of the above-described processing in the monitoring unit may be performed using, for example, AI, or may be performed without using AI. For example, the monitoring unit can input data on the baby's movements into a generation AI and cause the generation AI to learn the movement patterns.

[0097] The monitoring unit can monitor the baby's body temperature and notify if there is an abnormality. For example, the monitoring unit notifies if the baby's body temperature is too high. The monitoring unit can also notify if the baby's body temperature is too low. The monitoring unit can also notify if there is a sudden change in the baby's body temperature. In this way, by monitoring the baby's body temperature, abnormalities in body temperature can be detected early. Some or all of the above-mentioned processing in the monitoring unit may be performed using AI, for example, or may be performed without using AI. For example, the monitoring unit can input the baby's body temperature data into the generation AI and have the generation AI analyze the body temperature.

[0098] The monitoring unit can monitor the baby's sleep cycle and provide an optimal sleeping environment. For example, the monitoring unit can keep the environment quiet when the baby enters a deep sleep. The monitoring unit can also make the environment a little brighter when the baby enters a light sleep. The monitoring unit can also brighten the environment when the baby wakes up to make it easier for the baby to be active. In this way, by monitoring the baby's sleep cycle, an optimal sleeping environment can be provided. Some or all of the above-mentioned processing in the monitoring unit may be performed using, for example, AI, or may be performed without using AI. For example, the monitoring unit can input the baby's sleep data into the generation AI and have the generation AI analyze the sleep cycle.

[0099] The monitoring unit can estimate the baby's emotions and determine a monitoring priority based on the estimated baby's emotions. For example, if the baby feels anxious, the monitoring unit can set the monitoring priority to high. If the baby is relaxed, the monitoring unit can also set the monitoring priority to low. If the baby is excited, the monitoring unit can also set the monitoring priority to medium. This enables more appropriate monitoring by determining the monitoring priority according to the baby's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or a generation AI. The generation AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-mentioned processing in the monitoring unit can be performed using an AI, for example, or without an AI. For example, the monitoring unit can input the baby's facial expression data into the generation AI and cause the generation AI to estimate the emotion.

[0100] The monitoring unit can monitor sounds around the baby and notify the user if an abnormal sound is detected. For example, the monitoring unit notifies the user that a loud noise is generated around the baby. The monitoring unit can also notify the user that a specific sound (e.g., crying) is generated around the baby. The monitoring unit can also notify the user that a continuous sound is generated around the baby. By monitoring the sounds around the baby, abnormal sounds can be detected early. Some or all of the above-described processing in the monitoring unit may be performed using AI, for example, or may be performed without using AI. For example, the monitoring unit can input sound data around the baby to the generation AI and cause the generation AI to detect abnormal sounds.

[0101] The monitoring unit can monitor changes in the baby's weight and notify the user if an abnormality is detected. For example, the monitoring unit can notify the user that an abnormality has occurred if the baby's weight increases suddenly. The monitoring unit can also notify the user that an abnormality has occurred if the baby's weight decreases suddenly. The monitoring unit can also notify the user that an abnormality has occurred if the baby's weight does not change for a certain period of time. In this way, by monitoring changes in the baby's weight, weight abnormalities can be detected early. Some or all of the above-described processing in the monitoring unit may be performed using AI, for example, or may be performed without using AI. For example, the monitoring unit can input the baby's weight data into the generation AI and have the generation AI analyze the weight.

[0102] The monitoring unit can automatically create a baby's growth record and provide it to the parents. The monitoring unit can, for example, record changes in the baby's weight and height and periodically report them to the parents. The monitoring unit can also record the baby's sleep patterns and provide them to the parents. The monitoring unit can also automatically create a record of the baby's meals and provide them to the parents. In this way, by automatically creating a baby's growth record, it is possible to provide convenient information to the parents. Some or all of the above-mentioned processing in the monitoring unit may be performed using, for example, AI, or may be performed without using AI. For example, the monitoring unit can input the baby's growth data into the generation AI and cause the generation AI to create a growth record.

[0103] The notification unit can estimate the emotions of the parents and adjust the urgency of the notification based on the estimated emotions of the parents. For example, if the parents are stressed, the notification unit can send only notifications with a high level of urgency. Furthermore, if the parents are relaxed, the notification unit can also send all notifications. Furthermore, if the parents are busy, the notification unit can also send only notifications with a high level of urgency. This allows for more appropriate notifications by adjusting the urgency of notifications according to the emotions of the parents. The emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-described processing in the notification unit can be performed using, for example, AI, or without AI. For example, the notification unit can input facial expression data of the parents into the generation AI and have the generation AI estimate the emotions.

[0104] The notification unit can customize the notification content and provide a notification method that suits the parents' preferences. For example, the notification unit selects a notification method (e.g., voice, text) preferred by the parents and provides the notification. The notification unit can also select notification content (e.g., detailed information, concise information) preferred by the parents and provide the notification. The notification unit can also select a notification timing (e.g., real-time, periodic) preferred by the parents and provide the notification. This allows for more appropriate notification by providing a notification method that suits the parents' preferences. Some or all of the above-described processing in the notification unit may be performed using, or without, AI. For example, the notification unit can input parents' preference data into a generation AI and have the generation AI customize the notification content.

[0105] The notification unit can analyze the notification history and learn the optimal notification timing. For example, the notification unit can analyze the timing of notifications received by the parents in the past and suggest the optimal notification timing. The notification unit can also analyze the content of notifications received by the parents in the past and suggest the optimal notification content. The notification unit can also analyze the method of notification received by the parents in the past and suggest the optimal notification method. In this way, the optimal notification timing can be learned by analyzing the notification history. Some or all of the above-mentioned processing in the notification unit may be performed using, for example, AI, or may be performed without using AI. For example, the notification unit can input notification history data to a generation AI and cause the generation AI to learn the optimal notification timing.

[0106] The notification unit can report the baby's current condition in detail when notifying. For example, the notification unit can report the baby's body temperature and breathing condition in detail. The notification unit can also report the baby's sleeping condition and movements in detail. The notification unit can also report the baby's surrounding environment (temperature, humidity, illuminance) in detail. This allows parents to accurately understand the situation by reporting the baby's current condition in detail. Some or all of the above-mentioned processing in the notification unit may be performed using AI, for example, or may be performed without using AI. For example, the notification unit can input data from each sensor into the generation AI and have the generation AI execute a detailed report of the baby's condition.

[0107] The notification unit can estimate the emotions of the parents and adjust the content of the notification based on the estimated emotions of the parents. For example, if the parents are stressed, the notification unit can provide concise notification content. If the parents are relaxed, the notification unit can also provide detailed notification content. If the parents are busy, the notification unit can also notify only important information. This allows for more appropriate notification by adjusting the content of the notification according to the emotions of the parents. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-mentioned processing in the notification unit can be performed using AI, for example, or without AI. For example, the notification unit can input facial expression data of the parents into the generation AI and have the generation AI perform emotion estimation.

[0108] The notification unit can also provide environmental information about the baby's surroundings when making a notification. For example, the notification unit can notify the temperature and humidity around the baby. The notification unit can also notify the illuminance around the baby. The notification unit can also notify the sound environment around the baby. By providing environmental information about the baby's surroundings, parents can accurately understand the situation. Some or all of the above-mentioned processing in the notification unit can be performed using AI, for example, or without AI. For example, the notification unit can input data from each sensor into the generation AI and cause the generation AI to provide environmental information.

[0109] The notification unit can display a graph of the progress of the baby's health condition at the time of notification. The notification unit can, for example, display a graph of the progress of the baby's body temperature. The notification unit can also display a graph of the progress of the baby's breathing condition. The notification unit can also display a graph of the progress of the baby's sleeping condition. By displaying a graph of the progress of the baby's health condition, parents can visually grasp the situation. Some or all of the above-mentioned processing in the notification unit can be performed, for example, using AI or without using AI. For example, the notification unit can input data from each sensor into the generation AI and cause the generation AI to display a graph of the progress of the health condition.

[0110] The notification unit can provide advice according to the baby's condition at the time of notification. For example, if the baby's body temperature is high, the notification unit can advise cooling methods. The notification unit can also advise consulting a doctor if the baby's breathing is irregular. The notification unit can also advise how to improve the baby's environment if the baby is not sleeping well. This allows parents to take appropriate action by providing advice according to the baby's condition. Some or all of the above-mentioned processing in the notification unit may be performed using, or without, AI. For example, the notification unit can input data from each sensor into a generation AI and cause the generation AI to generate advice.

[0111] The detection unit can estimate the baby's emotion and adjust the breathing detection accuracy based on the estimated emotion. For example, if the baby is feeling anxious, the detection unit can increase the breathing detection accuracy. If the baby is relaxed, the detection unit can also decrease the breathing detection accuracy. If the baby is excited, the detection unit can maintain a medium level of breathing detection accuracy. This allows for more accurate detection by adjusting the breathing detection accuracy according to the baby's emotion. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or a generation AI. The generation AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to these examples. Some or all of the above-mentioned processing in the detection unit may be performed using an AI, for example, or without an AI. For example, the detection unit can input the baby's facial expression data into the generation AI and cause the generation AI to estimate the emotion.

[0112] The detection unit can detect the baby's heart rate and notify if there is an abnormality. For example, the detection unit can notify if the baby's heart rate is too high. The detection unit can also notify if the baby's heart rate is too low. The detection unit can also notify if there is a sudden change in the baby's heart rate. In this way, by detecting the baby's heart rate, heart rate abnormalities can be detected early. Some or all of the above-mentioned processing in the detection unit may be performed using AI, for example, or may be performed without using AI. For example, the detection unit can input the baby's heart rate data to the generation AI and have the generation AI analyze the heart rate.

[0113] The detection unit can detect the baby's body movements and notify if there is an abnormality. For example, the detection unit can notify as an abnormality if the baby moves in a way that deviates from normal movements. The detection unit can also notify as an abnormality if the baby moves in a way that deviates from a pattern of specific movements during a specific time period. The detection unit can also determine whether a specific movement is abnormal if the baby repeats it. In this way, by detecting the baby's body movements, abnormal movements can be detected early. Some or all of the above-mentioned processing in the detection unit may be performed using, for example, AI, or may be performed without using AI. For example, the detection unit can input the baby's body movement data to the generation AI and have the generation AI analyze the body movements.

[0114] The detection unit can detect the baby's skin color and notify if there is an abnormality. For example, the detection unit can notify if the baby's skin color turns pale. The detection unit can also notify if the baby's skin color turns red. The detection unit can also notify if there is a sudden change in the baby's skin color. In this way, by detecting the baby's skin color, skin abnormalities can be detected early. Some or all of the above-mentioned processing in the detection unit may be performed using AI, for example, or may be performed without using AI. For example, the detection unit can input the baby's skin color data to the generation AI and cause the generation AI to analyze the skin color.

[0115] The detection unit can estimate the baby's emotion and adjust the breathing detection frequency based on the estimated emotion. For example, if the baby is feeling anxious, the detection unit can increase the breathing detection frequency. If the baby is relaxed, the detection unit can also decrease the breathing detection frequency. If the baby is excited, the detection unit can maintain a medium breathing detection frequency. This allows for more accurate detection by adjusting the breathing detection frequency according to the baby's emotion. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to these examples. Some or all of the above-mentioned processing in the detection unit may be performed using an AI, for example, or without an AI. For example, the detection unit can input the baby's facial expression data into the generation AI and cause the generation AI to estimate the emotion.

[0116] The detection unit can detect the baby's body temperature and notify if there is an abnormality. For example, the detection unit can notify if the baby's body temperature is too high. The detection unit can also notify if the baby's body temperature is too low. The detection unit can also notify if there is a sudden change in the baby's body temperature. In this way, by detecting the baby's body temperature, abnormalities in body temperature can be detected early. Some or all of the above-mentioned processing in the detection unit may be performed using AI, for example, or may be performed without using AI. For example, the detection unit can input the baby's body temperature data into the generation AI and have the generation AI analyze the body temperature.

[0117] The detection unit can detect the baby's sleep state and notify the user if an abnormality is detected. For example, the detection unit can notify the user that an abnormality exists if the baby deviates from a normal sleep pattern. The detection unit can also notify the user that an abnormality exists if the baby does not exhibit a specific sleep pattern during a specific time period. The detection unit can also notify the user that an abnormality exists if the baby makes abnormal movements while sleeping. In this way, by detecting the baby's sleep state, sleep abnormalities can be detected early. Some or all of the above-described processing in the detection unit may be performed using AI, for example, or may be performed without using AI. For example, the detection unit can input the baby's sleep data into the generation AI and have the generation AI analyze the sleep state.

[0118] The detection unit can automatically create a baby's growth record and provide it to the parents. The detection unit can, for example, record changes in the baby's weight and height and periodically report them to the parents. The detection unit can also record the baby's sleep patterns and provide them to the parents. The detection unit can also automatically create a record of the baby's meals and provide them to the parents. In this way, by automatically creating a baby's growth record, it is possible to provide useful information to the parents. Some or all of the above-mentioned processing in the detection unit may be performed using AI, for example, or may be performed without using AI. For example, the detection unit can input the baby's growth data into the generation AI and cause the generation AI to create a growth record.

[0119] The monitoring unit can estimate the baby's emotions and adjust the frequency of environmental monitoring based on the estimated baby's emotions. For example, if the baby feels anxious, the monitoring unit can increase the frequency of environmental monitoring. If the baby is relaxed, the monitoring unit can also decrease the frequency of environmental monitoring. If the baby is excited, the monitoring unit can maintain a medium frequency of environmental monitoring. This allows for more appropriate monitoring by adjusting the frequency of environmental monitoring according to the baby's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-mentioned processing in the monitoring unit can be performed using AI, for example, or without AI. For example, the monitoring unit can input the baby's facial expression data into the generation AI and cause the generation AI to estimate the emotion.

[0120] The monitoring unit can monitor the sound environment around the baby and notify if there is an abnormality. For example, the monitoring unit notifies if a loud noise occurs around the baby. The monitoring unit can also notify if a specific sound (e.g., crying) occurs around the baby. The monitoring unit can also notify if a continuous sound occurs around the baby. In this way, by monitoring the sound environment around the baby, abnormal sounds can be detected early. Some or all of the above-mentioned processing in the monitoring unit may be performed using AI, for example, or may be performed without using AI. For example, the monitoring unit can input sound data around the baby to the generation AI and cause the generation AI to detect abnormal sounds.

[0121] The monitoring unit can monitor the air quality in the baby's bedroom and notify the user if an abnormality is detected. For example, the monitoring unit can notify the user if the carbon dioxide concentration in the air in the baby's bedroom is too high. The monitoring unit can also notify the user if the formaldehyde concentration in the air in the baby's bedroom is too high. The monitoring unit can also notify the user if the particulate concentration in the air in the baby's bedroom is too high. In this way, by monitoring the air quality in the baby's bedroom, abnormalities in the air quality can be detected early. Some or all of the above-described processing in the monitoring unit may be performed using, or without, AI. For example, the monitoring unit can input air quality data to a generation AI and have the generation AI perform an air quality analysis.

[0122] The monitoring unit can monitor the lighting conditions in the baby's bedroom and provide an optimal lighting environment. For example, the monitoring unit can dim the lights at night to make it easier for the baby to sleep. The monitoring unit can also brighten the lights in the morning to make it easier for the baby to wake up. The monitoring unit can also maintain a moderate brightness during the day to make it easier for the baby to be active. In this way, by monitoring the lighting conditions in the baby's bedroom, an optimal lighting environment can be provided. Some or all of the above-mentioned processing in the monitoring unit may be performed using, for example, AI, or may be performed without using AI. For example, the monitoring unit can input lighting condition data into the generation AI and cause the generation AI to analyze the lighting environment.

[0123] The monitoring unit can estimate the baby's emotions and determine the priority of environmental monitoring based on the estimated baby's emotions. For example, if the baby feels anxious, the monitoring unit can set the priority of environmental monitoring to high. If the baby is relaxed, the monitoring unit can also set the priority of environmental monitoring to low. If the baby is excited, the monitoring unit can also set the priority of environmental monitoring to medium. This enables more appropriate monitoring by determining the priority of environmental monitoring according to the baby's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or a generation AI. The generation AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-mentioned processing in the monitoring unit can be performed using AI, for example, or without AI. For example, the monitoring unit can input the baby's facial expression data into the generation AI and cause the generation AI to estimate the emotion.

[0124] The monitoring unit can monitor temperature changes in the baby's bedroom and notify the user if an abnormality is detected. For example, the monitoring unit can notify the user that an abnormality exists if the temperature in the baby's bedroom is too high. The monitoring unit can also notify the user that an abnormality exists if the temperature in the baby's bedroom is too low. The monitoring unit can also notify the user that an abnormality exists if the temperature in the baby's bedroom changes suddenly. In this way, by monitoring temperature changes in the baby's bedroom, temperature abnormalities can be detected early. Some or all of the above-described processing in the monitoring unit may be performed using AI, for example, or may be performed without using AI. For example, the monitoring unit can input temperature data into the generation AI and have the generation AI analyze the temperature changes.

[0125] The monitoring unit can monitor humidity changes in the baby's bedroom and notify the user if an abnormality is detected. For example, the monitoring unit can notify the user that the humidity in the baby's bedroom is too high. The monitoring unit can also notify the user that the humidity in the baby's bedroom is too low. The monitoring unit can also notify the user that the humidity in the baby's bedroom changes suddenly. In this way, by monitoring humidity changes in the baby's bedroom, humidity abnormalities can be detected early. Some or all of the above-described processing in the monitoring unit can be performed using AI, for example, or can be performed without using AI. For example, the monitoring unit can input humidity data to the generation AI and have the generation AI analyze the humidity changes.

[0126] The control unit can estimate the baby's emotions and adjust the environmental control method based on the estimated baby's emotions. For example, if the baby feels anxious, the control unit can keep the environment quiet. If the baby feels relaxed, the control unit can also make the environment slightly brighter. If the baby is excited, the control unit can also keep the environment at a moderate level. This allows for providing a more appropriate environment by adjusting the environmental control method according to the baby's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or a generative AI. The generative AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-mentioned processing in the control unit may be performed using an AI, for example, or without using an AI. For example, the control unit can input the baby's facial expression data into the generative AI and cause the generative AI to estimate the emotion.

[0127] The control unit can adjust the air conditioner settings based on the baby's body temperature. For example, if the baby's body temperature is too high, the control unit can lower the temperature of the air conditioner. The control unit can also raise the temperature of the air conditioner if the baby's body temperature is too low. The control unit can also adjust the air conditioner settings if the baby's body temperature changes suddenly. In this way, an appropriate temperature environment can be provided by adjusting the air conditioner settings based on the baby's body temperature. Some or all of the above-mentioned processing in the control unit may be performed using AI, for example, or may be performed without using AI. For example, the control unit can input the baby's body temperature data into the generation AI and have the generation AI adjust the air conditioner settings.

[0128] The control unit can adjust the brightness of the lighting based on the baby's sleep state. For example, the control unit dims the lighting at night to make it easier for the baby to sleep. The control unit can also brighten the lighting in the morning to make it easier for the baby to wake up. The control unit can also maintain a moderate brightness during the day to make it easier for the baby to be active. In this way, an optimal sleeping environment can be provided by adjusting the brightness of the lighting based on the baby's sleep state. Some or all of the above-mentioned processing in the control unit may be performed using, for example, AI, or may be performed without using AI. For example, the control unit can input the baby's sleep data into the generation AI and have the generation AI adjust the brightness of the lighting.

[0129] The control unit can adjust the humidifier settings based on the baby's breathing condition. For example, the control unit adjusts the humidifier settings when the baby's breathing is irregular. The control unit can also maintain the humidifier settings when the baby's breathing is normal. The control unit can also change the humidifier settings when the baby's breathing has stopped. In this way, an appropriate humidity environment can be provided by adjusting the humidifier settings based on the baby's breathing condition. Some or all of the above-mentioned processing in the control unit may be performed using AI, for example, or may be performed without using AI. For example, the control unit can input the baby's breathing data into the generation AI and cause the generation AI to adjust the humidifier settings.

[0130] The control unit can estimate the baby's emotions and determine the priority of environmental control based on the estimated baby's emotions. For example, if the baby feels anxious, the control unit can set the priority of environmental control to high. If the baby is relaxed, the control unit can also set the priority of environmental control to low. If the baby is excited, the control unit can also set the priority of environmental control to medium. This allows for determining the priority of environmental control according to the baby's emotions, thereby providing a more appropriate environment. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or a generative AI. The generative AI may be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-mentioned processing in the control unit may be performed using an AI, for example, or without an AI. For example, the control unit can input the baby's facial expression data into the generative AI and cause the generative AI to estimate the emotion.

[0131] The control unit can control the noise canceling function based on the sound environment around the baby. For example, the control unit can enhance the noise canceling function when a loud noise occurs around the baby. The control unit can also maintain the noise canceling function when a quiet environment is required around the baby. The control unit can also adjust the noise canceling function when continuous noise occurs around the baby. In this way, an appropriate sound environment can be provided by controlling the noise canceling function based on the sound environment around the baby. Some or all of the above-mentioned processing in the control unit can be performed using, for example, AI, or can be performed without using AI. For example, the control unit can input sound environment data to a generation AI and cause the generation AI to control the noise canceling function.

[0132] The control unit can control the air purifier based on the air quality in the baby's bedroom. For example, the control unit can activate the air purifier when the carbon dioxide concentration in the air in the baby's bedroom is too high. The control unit can also activate the air purifier when the formaldehyde concentration in the air in the baby's bedroom is too high. The control unit can also activate the air purifier when the particulate concentration in the air in the baby's bedroom is too high. In this way, an appropriate air environment can be provided by controlling the air purifier based on the air quality in the baby's bedroom. Some or all of the above-mentioned processing in the control unit can be performed, for example, using AI or without AI. For example, the control unit can input air quality data to the generation AI and have the generation AI control the air purifier.

[0133] The control unit can control the opening and closing of curtains based on the lighting conditions in the baby's bedroom. For example, the control unit closes the curtains at night to make it easier for the baby to sleep. The control unit can also open the curtains in the morning to make it easier for the baby to wake up. The control unit can also open the curtains moderately during the day to make it easier for the baby to be active. In this way, an appropriate lighting environment can be provided by controlling the opening and closing of curtains based on the lighting conditions in the baby's bedroom. Some or all of the above-mentioned processing in the control unit may be performed using, for example, AI, or may be performed without using AI. For example, the control unit can input lighting condition data into the generation AI and cause the generation AI to control the opening and closing of curtains.

[0134] The management unit can estimate the baby's emotions and adjust the data analysis method based on the estimated baby's emotions. For example, if the baby is feeling anxious, the management unit can increase the frequency of data analysis. If the baby is relaxed, the management unit can also decrease the frequency of data analysis. If the baby is excited, the management unit can maintain a medium frequency of data analysis. This allows for more appropriate analysis by adjusting the data analysis method according to the baby's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generative AI. The generative AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-mentioned processing in the management unit can be performed using AI, for example, or without AI. For example, the management unit can input the baby's facial expression data into the generative AI and have the generative AI perform emotion estimation.

[0135] The management unit can integrate data from each sensor and comprehensively evaluate the baby's health condition. For example, the management unit can integrate data on the baby's body temperature, breathing, and heart rate to evaluate the health condition. The management unit can also integrate data on the baby's sleep state, body movement, and skin color to evaluate the health condition. The management unit can also integrate environmental data (temperature, humidity, illuminance) around the baby to evaluate the health condition. In this way, by integrating data from each sensor, the baby's health condition can be comprehensively evaluated. Some or all of the above-mentioned processing in the management unit may be performed using, or without, a generation AI. For example, the management unit can input data from each sensor into the generation AI and have the generation AI integrate and evaluate the data.

[0136] The management unit can analyze past data and predict the baby's health condition. For example, the management unit can analyze the baby's past body temperature data and predict future changes in body temperature. The management unit can also analyze the baby's past breathing data and predict future breathing conditions. The management unit can also analyze the baby's past sleep data and predict future sleep patterns. This makes it possible to predict the baby's health condition by analyzing past data. Some or all of the above-mentioned processing in the management unit may be performed using, for example, a generation AI, or may be performed without using a generation AI. For example, the management unit can input past data into the generation AI and have the generation AI execute a health condition prediction.

[0137] The management unit can provide advice to parents based on the baby's health condition. For example, if the baby's body temperature is high, the management unit can advise how to cool the baby. The management unit can also advise the parents to consult a doctor if the baby's breathing is irregular. The management unit can also advise how to improve the baby's environment if the baby is not sleeping well. In this way, by providing advice based on the baby's health condition, parents can take appropriate action. Some or all of the above-mentioned processing in the management unit may be performed using, or without, a generation AI. For example, the management unit can input health condition data into the generation AI and cause the generation AI to generate advice.

[0138] The management unit can estimate the baby's emotions and determine the priority of data analysis based on the estimated baby's emotions. For example, if the baby is feeling anxious, the management unit can set the priority of data analysis to high. If the baby is relaxed, the management unit can also set the priority of data analysis to low. If the baby is excited, the management unit can also set the priority of data analysis to medium. This enables more appropriate analysis by determining the priority of data analysis according to the baby's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or a generative AI. The generative AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-mentioned processing in the management unit can be performed using an AI, for example, or without an AI. For example, the management unit can input the baby's facial expression data into the generative AI and have the generative AI perform emotion estimation.

[0139] The management unit can integrate data from each sensor and automatically create a baby's growth record. The management unit, for example, records changes in the baby's weight and height and periodically reports them to the parents. The management unit can also record the baby's sleep patterns and provide them to the parents. The management unit can also automatically create a record of the baby's meals and provide them to the parents. In this way, by integrating data from each sensor, a baby's growth record can be automatically created. Some or all of the above-mentioned processing in the management unit may be performed using, or without, a generation AI. For example, the management unit can input data from each sensor into the generation AI and have the generation AI create a growth record.

[0140] The management unit analyzes data from each sensor and can detect abnormalities in the baby's health at an early stage. For example, the management unit analyzes the baby's body temperature data and can detect abnormalities at an early stage. The management unit can also analyze the baby's breathing data and can detect abnormalities at an early stage. The management unit can also analyze the baby's sleep data and can detect abnormalities at an early stage. In this way, by analyzing the data from each sensor, abnormalities in the baby's health can be detected at an early stage. Some or all of the above-mentioned processing in the management unit may be performed using, for example, a generation AI, or may be performed without using a generation AI. For example, the management unit can input data from each sensor into the generation AI and have the generation AI detect abnormalities.

[0141] The management unit can create a health status report of the baby based on data from each sensor and provide it to the parents. The management unit can create a health status report based on data on the baby's body temperature, breathing, and heart rate, for example. The management unit can also create a health status report based on data on the baby's sleep state, body movement, and skin color. The management unit can also create a health status report based on environmental data (temperature, humidity, illuminance) around the baby. In this way, by creating a health status report based on data from each sensor, parents can accurately understand the baby's health status. Some or all of the above-mentioned processing in the management unit may be performed using, or without, a generation AI, for example. For example, the management unit can input data from each sensor into the generation AI and cause the generation AI to create a health status report. === Hard Collateral 1-1 === Each of the multiple elements, including the above-described monitoring unit, notification unit, detection unit, monitoring unit, control unit, and management unit, is realized, for example, in at least one of the smart device 14 and the data processing device 12. For example, the monitoring unit can monitor the baby's movements using the camera 42 of the smart device 14 and detect an abnormality using the specific processing unit 290 of the data processing device 12. For example, the notification unit can send an alert to the parents via the control unit 46A of the smart device 14 and notify them of the abnormality using the specific processing unit 290 of the data processing device 12. For example, the detection unit can detect the baby's breathing using a vibration sensor of the smart device 14 and detect an abnormality using the specific processing unit 290 of the data processing device 12. For example, the monitoring unit can monitor the environment in the baby's bedroom using a temperature and humidity sensor of the smart device 14 and detect an abnormality using the specific processing unit 290 of the data processing device 12. For example, the control unit can control an air conditioner or humidifier via the control unit 46A of the smart device 14 and control the environment using the specific processing unit 290 of the data processing device 12. For example, the management unit can integrate data from each sensor of the smart device 14 and manage the overall condition of the baby by the specific processing unit 290 of the data processing device 12. === Hard Collateral 1-2 === Each of the multiple elements including the above-described monitoring unit, notification unit, detection unit, monitoring unit, control unit, and management unit is realized, for example, in at least one of the smart glasses 214 and the data processing device 12. For example, the monitoring unit can monitor the baby's movements using the camera 42 of the smart glasses 214 and detect an abnormality using the specific processing unit 290 of the data processing device 12. For example, the notification unit can send an alert to the parents via the control unit 46A of the smart glasses 214 and notify them of the abnormality using the specific processing unit 290 of the data processing device 12. For example, the detection unit can detect the baby's breathing using a vibration sensor of the smart glasses 214 and detect an abnormality using the specific processing unit 290 of the data processing device 12. For example, the monitoring unit can monitor the environment of the baby's bedroom using a temperature and humidity sensor of the smart glasses 214 and detect an abnormality using the specific processing unit 290 of the data processing device 12. For example, the control unit can control an air conditioner or humidifier via the control unit 46A of the smart glasses 214 and control the environment using the specific processing unit 290 of the data processing device 12. For example, the management unit can integrate data from each sensor of the smart glasses 214 and manage the overall condition of the baby through the specific processing unit 290 of the data processing device 12. === Hard Collateral 1-3 === Each of the multiple elements including the above-mentioned monitoring unit, notification unit, detection unit, monitoring unit, control unit, and management unit is realized, for example, in at least one of the headset-type terminal 314 and the data processing device 12. For example, the monitoring unit can monitor the baby's movements using the camera 42 of the headset-type terminal 314 and detect an abnormality using the specific processing unit 290 of the data processing device 12. For example, the notification unit can send an alert to the parents via the control unit 46A of the headset-type terminal 314 and notify them of the abnormality using the specific processing unit 290 of the data processing device 12. For example, the detection unit can detect the baby's breathing using a vibration sensor of the headset-type terminal 314 and detect an abnormality using the specific processing unit 290 of the data processing device 12. For example, the monitoring unit can monitor the environment in the baby's bedroom using a temperature and humidity sensor of the headset-type terminal 314 and detect an abnormality using the specific processing unit 290 of the data processing device 12. For example, the control unit can control an air conditioner or a humidifier via the control unit 46A of the headset-type terminal 314 and control the environment using the specific processing unit 290 of the data processing device 12. For example, the management unit can integrate data from each sensor of the headset type terminal 314 and manage the overall condition of the baby using the specific processing unit 290 of the data processing device 12. === Hard Collateral 1-4 === Each of the multiple elements including the above-mentioned monitoring unit, notification unit, detection unit, monitoring unit, control unit, and management unit is realized, for example, in at least one of the robot 414 and the data processing device 12. For example, the monitoring unit can monitor the baby's movements using the camera 42 of the robot 414 and detect an abnormality using the specific processing unit 290 of the data processing device 12. For example, the notification unit can send an alert to the parents via the control unit 46A of the robot 414 and notify them of the abnormality using the specific processing unit 290 of the data processing device 12. For example, the detection unit can detect the baby's breathing using a vibration sensor of the robot 414 and detect an abnormality using the specific processing unit 290 of the data processing device 12. For example, the monitoring unit can monitor the environment of the baby's bedroom using a temperature and humidity sensor of the robot 414 and detect an abnormality using the specific processing unit 290 of the data processing device 12. For example, the control unit can control an air conditioner or a humidifier via the control unit 46A of the robot 414 and control the environment using the specific processing unit 290 of the data processing device 12. For example, the management unit can integrate data from each sensor of the robot 414 and manage the overall condition of the baby using the specific processing unit 290 of the data processing device 12.

[0142] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0143] The monitoring unit can monitor the baby's body temperature and notify the user if there is an abnormality. For example, if the baby's body temperature is too high, it notifies the user that there is an abnormality. The monitoring unit can also notify the user that there is an abnormality if the baby's body temperature is too low. The monitoring unit can also notify the user that there is an abnormality if there is a sudden change in the baby's body temperature. In this way, by monitoring the baby's body temperature, abnormalities in body temperature can be detected early. Some or all of the above-mentioned processing in the monitoring unit may be performed using AI, for example, or may be performed without using AI. For example, the monitoring unit can input the baby's body temperature data into the generation AI and have the generation AI analyze the body temperature.

[0144] The notification unit can estimate the baby's emotions and adjust the urgency of the notification based on the estimated baby's emotions. For example, if the baby is feeling anxious, a high-urgency notification can be sent. If the baby is relaxed, a low-urgency notification can be sent. If the baby is excited, the urgency can be set to medium. This allows for more appropriate notifications by adjusting the urgency of the notification according to the baby's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-mentioned processing in the notification unit can be performed using AI, for example, or without AI. For example, the notification unit can input the baby's facial expression data into the generation AI and have the generation AI perform emotion estimation.

[0145] The detection unit can detect the baby's heart rate and notify the user if an abnormality is detected. For example, if the baby's heart rate is too high, the detection unit can notify the user that an abnormality exists. The detection unit can also notify the user that an abnormality exists if the baby's heart rate is too low. The detection unit can also notify the user that an abnormality exists if the baby's heart rate changes suddenly. In this way, by detecting the baby's heart rate, abnormalities in the heart rate can be detected early. Some or all of the above-described processing in the detection unit may be performed using AI, for example, or may be performed without using AI. For example, the detection unit can input the baby's heart rate data to the generation AI and have the generation AI analyze the heart rate.

[0146] The monitoring unit can estimate the baby's emotions and adjust the frequency of environmental monitoring based on the estimated baby's emotions. For example, if the baby feels anxious, the frequency of environmental monitoring can be increased. If the baby is relaxed, the frequency of environmental monitoring can be decreased. If the baby is excited, the frequency of environmental monitoring can be kept at a moderate level. This allows for more appropriate monitoring by adjusting the frequency of environmental monitoring according to the baby's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-mentioned processing in the monitoring unit can be performed using AI, for example, or without AI. For example, the monitoring unit can input the baby's facial expression data into the generation AI and cause the generation AI to estimate the emotion.

[0147] The control unit can estimate the baby's emotions and adjust the environmental control method based on the estimated baby's emotions. For example, if the baby feels anxious, the environment can be kept quiet. If the baby is relaxed, the environment can be made slightly brighter. If the baby is excited, the environment can be kept moderate. This allows for a more appropriate environment to be provided by adjusting the environmental control method according to the baby's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-mentioned processing in the control unit can be performed using AI, for example, or without AI. For example, the control unit can input the baby's facial expression data into the generation AI and cause the generation AI to estimate the emotion.

[0148] The management unit can integrate data from each sensor and comprehensively evaluate the baby's health condition. For example, it can integrate data on the baby's body temperature, breathing, and heart rate to evaluate the health condition. The management unit can also integrate data on the baby's sleep state, body movement, and skin color to evaluate the health condition. The management unit can also integrate environmental data (temperature, humidity, illuminance) around the baby to evaluate the health condition. In this way, by integrating data from each sensor, the baby's health condition can be comprehensively evaluated. Some or all of the above-mentioned processing in the management unit may be performed using, or without, a generation AI. For example, the management unit can input data from each sensor into the generation AI and have the generation AI integrate and evaluate the data.

[0149] The notification unit can customize the notification content and provide a notification method that suits the parents' preferences. For example, the notification unit selects the notification method (e.g., voice, text) preferred by the parents and provides the notification. The notification unit can also select the notification content (e.g., detailed information, concise information) preferred by the parents and provide the notification. The notification unit can also select the notification timing (e.g., real-time, periodic) preferred by the parents and provide the notification. This allows for more appropriate notification by providing a notification method that suits the parents' preferences. Some or all of the above-described processing in the notification unit may be performed using AI, for example, or may be performed without using AI. For example, the notification unit can input the parents' preference data into the generation AI and have the generation AI customize the notification content.

[0150] The detection unit can monitor changes in the baby's weight and notify if there is an abnormality. For example, if the baby's weight increases suddenly, it notifies as an abnormality. The detection unit can also notify as an abnormality if the baby's weight decreases suddenly. The detection unit can also notify as an abnormality if the baby's weight does not change for a certain period of time. In this way, by monitoring changes in the baby's weight, weight abnormalities can be detected early. Some or all of the above-mentioned processing in the detection unit may be performed using AI, for example, or may be performed without using AI. For example, the detection unit can input the baby's weight data into the generation AI and have the generation AI perform weight analysis.

[0151] The monitoring unit can monitor the air quality in the baby's bedroom and notify the user if an abnormality is detected. For example, if the carbon dioxide concentration in the air in the baby's bedroom is too high, the monitoring unit can notify the user as an abnormality. The monitoring unit can also notify the user as an abnormality if the formaldehyde concentration in the air in the baby's bedroom is too high. The monitoring unit can also notify the user as an abnormality if the particulate concentration in the air in the baby's bedroom is too high. In this way, by monitoring the air quality in the baby's bedroom, abnormalities in the air quality can be detected early. Some or all of the above-described processing in the monitoring unit may be performed using, or without, AI. For example, the monitoring unit can input air quality data to the generation AI and have the generation AI perform an air quality analysis.

[0152] The management unit can analyze past data and predict the baby's health condition. For example, it can analyze the baby's past body temperature data and predict future changes in body temperature. The management unit can also analyze the baby's past breathing data and predict future breathing conditions. The management unit can also analyze the baby's past sleep data and predict future sleep patterns. This makes it possible to predict the baby's health condition by analyzing past data. Some or all of the above-mentioned processing in the management unit may be performed using, for example, a generation AI, or may be performed without using a generation AI. For example, the management unit can input past data into the generation AI and have the generation AI perform a health condition prediction.

[0153] The processing flow of the second embodiment will be briefly explained below.

[0154] Step 1: The monitoring unit monitors the baby's movements using a camera. For example, it can monitor the baby's movements in real time and detect abnormalities such as when the baby lies face down or when the face is covered. It can also record the baby's movements and play them back later. Step 2: The notification unit notifies the parents of any abnormalities detected by the monitoring unit. For example, if the baby lies face down or covers its face, the notification unit will send an alert to the parents. It can also issue a voice alert or send a notification to a smartphone if an abnormality occurs. Step 3: The detector detects the baby's breathing using a vibration sensor. For example, it can monitor the baby's breathing in real time and detect abnormalities if it becomes irregular or stops. It can also record the baby's breathing and play it back later. Step 4: The monitoring unit constantly monitors the baby's bedroom environment using temperature and humidity sensors. For example, it monitors the temperature and humidity in the bedroom in real time and detects abnormalities if they are not appropriate. It can also record the temperature and humidity and play them back later. Step 5: The control unit controls the environment based on the data obtained by the monitoring unit. For example, it turns on the air conditioner if the room temperature is too high, and turns on the humidifier if the humidity is too low. It can also stop the air conditioner if the room temperature is too low, and stop the humidifier if the humidity is too high. It can also control the air conditioner and humidifier simultaneously to maintain appropriate room temperature and humidity. Step 6: The illuminance monitoring unit monitors the brightness using an illuminance sensor. For example, it can monitor the brightness of a baby's bedroom in real time and detect an abnormality if it is not appropriate. It can also record the brightness and play it back later. Step 7: The lighting control unit controls the lighting based on the data obtained by the illuminance monitoring unit. For example, if the brightness is not appropriate, the lighting can be adjusted. Step 8: The management unit analyzes the data from each sensor and manages the baby's overall condition. For example, it checks whether the baby is breathing normally and whether the room temperature and humidity are appropriate. It can also monitor changes in the baby's health and environment in real time, record them, and play them back later.

[0155] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0156] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0157] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0158] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0159] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0160] 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.

[0161] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0162] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0163] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0164] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0165] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0166] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0167] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0168] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0169] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0170] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0171] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0172] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0173] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0174] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0175] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0176] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0177] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0178] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0179] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0180] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0181] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0182] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0183] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0184] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0185] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the identification processing unit 290 using these models.

[0186] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0187] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0188] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0189] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0190] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0191] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0192] 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.

[0193] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0194] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0195] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0196] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0197] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0198] The control object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0199] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0200] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0201] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0202] In the robot 414, the processor 46 performs the identification process. The storage 50 stores the identification program 60. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as the control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 also has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform the same process as the identification processing unit 290 using these models.

[0203] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0204] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0205] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0206] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0207] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0208] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0209] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0210] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0211] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0212] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0213] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0214] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0215] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0216] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0217] 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.

[0218] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0219] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0220] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0221] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0222] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0223] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0224] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0225] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[0226] [Explanation of symbols]

[0227] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. A monitoring unit that monitors the baby's movements with a camera, a notification unit that notifies an abnormality detected by the monitoring unit; A detection unit that detects the baby's breathing; a notification unit that notifies an abnormality detected by the detection unit; a monitoring unit that monitors the environment using a temperature and humidity sensor; a control unit that controls the environment based on the data obtained by the monitoring unit; an illuminance monitoring unit that monitors brightness using an illuminance sensor; an illumination control unit that controls illumination based on the data obtained by the illuminance monitoring unit; A management unit that analyzes data from each sensor and manages the baby's condition. A system characterized by:

2. The monitoring unit Monitor your baby's movements in real time with a camera 2. The system of claim 1.

3. The notification unit Alerts parents if baby lies on stomach or face is covered 2. The system of claim 1.

4. The detection unit Monitoring baby's breathing with vibration sensors 2. The system of claim 1.

5. The notification unit Notify parents if their baby's breathing becomes irregular or stops 2. The system of claim 1.

6. The monitoring unit Constantly monitor your baby's bedroom environment with a temperature and humidity sensor 2. The system of claim 1.

7. The control unit Activate the air conditioner when the room temperature exceeds the set temperature, and activate the humidifier when the humidity falls below the set value.

2. The system of claim 1.

8. The monitoring unit Monitor the brightness of your bedroom with a light sensor 2. The system of claim 1.

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