system

Abstract

We provide the system. [Solution] A means for generating music that is optimal for getting a baby to sleep, A monitoring system equipped with a camera and microphone for monitoring the baby's condition, Control means for measuring and controlling the baby's body temperature and room temperature, An analytical method for analyzing data on how babies fall asleep and feeding that data back into music generation, A notification method that alerts you when the baby falls asleep, A system that includes a warning mechanism to issue a warning when an anomaly is detected.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, the method including: receiving a user utterance; adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot; encoding the prompt; and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Putting a baby to sleep is a great burden for parents, especially at night. With conventional methods, it is difficult to consistently find an effective way to put the baby to sleep, often leading to sleep deprivation and stress. Also, it is difficult to continuously monitor the baby's health status all the time, and early detection of abnormalities is required. The purpose of this invention is to shorten the time involved in putting the baby to sleep, reduce the burden on parents, and ensure the safety of the baby.

Means for Solving the Problems

[0005] This invention utilizes AI-powered generation methods to create music optimized for each individual baby. It also employs a camera and microphone as monitoring tools to continuously observe the baby's condition. Furthermore, control tools appropriately manage the baby's body temperature and room temperature, and analysis tools utilize past data to enable effective music generation. Finally, notification and warning tools allow parents to be immediately alerted when the baby falls asleep or when an abnormality occurs, ensuring safe and effective sleep training.

[0006] "Generation means" refers to a method or apparatus for automatically generating music that is optimal for a baby.

[0007] "Monitoring means" refers to devices such as cameras and microphones used to observe the baby's condition in real time.

[0008] "Control means" refers to a method or device for appropriately adjusting the baby's body temperature and room temperature to optimize the environment.

[0009] "Analysis means" refers to a method or device for analyzing a baby's past data and feeding that data back into future music generation.

[0010] A "notification device" is a method or device used to inform parents when a baby has fallen asleep.

[0011] A "warning device" is a method or device for promptly alerting parents when an abnormality occurs in a baby. [Brief explanation of the drawing]

[0012] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3]It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Embodiments for Carrying Out the Invention

[0013] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0014] First, the terms used in the following description will be explained.

[0015] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units 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), and the like.

[0016] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0017] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs, various parameters, and the like. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0018] In the following embodiments, the numbered communication I / F (Interface) is an interface that includes a communication processor, an antenna, and the like. 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), or Bluetooth (registered trademark).

[0019] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0020] [First Embodiment]

[0021] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0022] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0023] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0024] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0025] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0026] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0027] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0028] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0029] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0030] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0031] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0032] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0033] The system of this invention integrates functions to assist in getting babies to sleep. Users can operate this system through a smartphone app. When the app is launched, the user enters the baby's basic information and preferred music type, and then begins the sleep-inducing process.

[0034] The server uses an AI algorithm to generate the most suitable lullaby for the baby based on user input data. This generation method analyzes past data and trends to select the most effective music. The generated lullaby is played through a speaker via the device.

[0035] The device monitors the baby's condition using a camera and microphone, and transmits the data to the server in real time. Sensors, acting as monitoring tools, detect the baby's movements and sounds, and check their status. The server analyzes this data to determine the baby's sleep state and provides feedback as needed.

[0036] Furthermore, thermography and temperature sensors monitor the baby's body temperature and room temperature. The control system adjusts air conditioning and other settings appropriately based on the temperature data to create a comfortable environment for the baby.

[0037] The server notifies the user via the device when it determines that the baby has fallen asleep. It also has a function to immediately send an alert if an abnormality is detected. For example, if the baby's body temperature exceeds a set threshold, the server can issue an alert and notify the user's device.

[0038] This system configuration automates the entire process of getting a baby to sleep, reducing the burden on parents while ensuring the baby's safety.

[0039] The following describes the processing flow.

[0040] Step 1:

[0041] The user launches the app on their smartphone and enters basic information about their baby (age, music preferences, etc.). This information is then sent from the app to the server.

[0042] Step 2:

[0043] The server uses an AI algorithm to generate the optimal lullaby based on the information received from the user. This lullaby is selected considering past success data and current trends.

[0044] Step 3:

[0045] The generated lullaby is sent from the server to the terminal. The terminal plays this music through its speakers, creating an environment that helps soothe the baby to sleep.

[0046] Step 4:

[0047] The device monitors the baby's condition using a camera and microphone and transmits the data to a server in real time. The monitoring method involves detecting the baby's movements and sounds.

[0048] Step 5:

[0049] The server analyzes the video and audio data sent from the terminal to determine the baby's sleep state. If necessary, it regenerates an appropriate lullaby.

[0050] Step 6:

[0051] Furthermore, a temperature sensor built into the device monitors the baby's body temperature and the room temperature. Based on this data, the server adjusts the air conditioner settings to maintain a comfortable environment.

[0052] Step 7:

[0053] The server sends a notification to the user via the device when it determines that the baby has fallen asleep safely. It also immediately sends an alert to the user if any abnormalities (such as a high fever or prolonged crying) are detected.

[0054] (Example 1)

[0055] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0056] In today's busy lifestyle, efficiently getting babies to sleep is a crucial challenge for caregivers. Traditional methods make it difficult to accurately assess a baby's condition and maintain an appropriate environment, placing a heavy burden on caregivers. Furthermore, there is a need for a way to respond quickly to any health problems in babies, but existing systems are insufficient to address this.

[0057] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0058] In this invention, the server includes a generation means for generating optimal music to soothe a baby to sleep, a monitoring means equipped with a video recording device and an audio acquisition device for monitoring the baby's condition, and an environmental adjustment means for measuring and controlling the baby's body temperature and room temperature. This makes it possible to reduce the burden on caregivers and ensure safe and comfortable sleep for babies by providing appropriate music and environmental adjustments while monitoring the baby's condition in real time.

[0059] "Generation method" refers to the function or technology that generates optimal music for putting babies to sleep. This includes processes that automatically generate music using AI models and data analysis technologies.

[0060] "Monitoring means" refers to a mechanism equipped with a video recording device and an audio acquisition device used to monitor the baby's condition. This allows for real-time observation of the baby's behavior and sounds.

[0061] "Environmental adjustment means" refers to a mechanism for measuring the baby's body temperature and room temperature and controlling them as needed. Specifically, this includes functions that maintain an appropriate indoor environment by operating thermosensors, air conditioners, etc.

[0062] "Information processing means" refers to a function that analyzes data from the time the baby falls asleep and feeds the results back into music generation. This includes a process that uses data analysis technology to enhance the effectiveness of music generation.

[0063] "Notification means" refers to a function that notifies the user when the baby falls asleep. Specifically, this includes sending alerts and notifications to smartphones and other devices.

[0064] "Alarming mechanisms" refer to functions that issue warnings when an abnormality is detected. This includes issuing alerts to quickly inform the user of any abnormalities in the baby's health or environment.

[0065] This invention is a system for effectively getting babies to sleep, combining AI-powered music generation with real-time monitoring. This system primarily operates through the collaboration of a server, terminals, and users.

[0066] The server uses a generative AI model to generate music best suited for babies. Users input basic information about their baby and their musical preferences through a smartphone app, and this data is sent to the server. The server analyzes past data and trends and automatically generates music based on this analysis. For example, if a user requests "relaxing piano music," the generative AI model will be prompted with the command, "Generate a soothing piano lullaby for babies."

[0067] Meanwhile, the device plays a role in monitoring the baby's condition. Equipped with a camera and microphone, the device monitors the baby's behavior and sends the data to a server. The server analyzes this data to determine the baby's sleep state and any abnormalities.

[0068] Furthermore, the server measures temperature and humidity and controls air conditioning and other appliances to properly manage the environment around the baby. Once the user sets the environmental conditions, the device's sensors measure the indoor environment, and the server automatically adjusts the settings after analysis.

[0069] These features allow users to help their babies sleep safely and comfortably, reducing the burden of childcare.

[0070] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0071] Step 1:

[0072] The user launches the smartphone app and enters the baby's basic information (name, age, favorite music genre). The entered data is sent to the server. This allows the server to obtain basic data for music generation based on the information received from the user. Specifically, if the user selects "classical music," this selection is passed from the smartphone to the server.

[0073] Step 2:

[0074] The server uses a generative AI model to generate music best suited for a baby, based on data from the user. Input includes the user's music genre selection and the baby's age, while output is a music file generated by the AI ​​model. For example, the prompt "Generate relaxing classical music" is input to the model, and the generated music data is output. Specifically, the AI ​​composes the music in the cloud, and the generated file is saved on the server.

[0075] Step 3:

[0076] The server sends the generated music to the device. The device receives this music and plays it through a speaker in the room where the baby is. The input here is music data from the AI ​​model, and the output is the sound of the music being played. The music starts playing from the device's speaker, and the volume and playback time follow conditions set by the user beforehand.

[0077] Step 4:

[0078] The device sends data from its camera and microphone to a server to monitor the baby's condition. This monitoring data includes the baby's movements and sounds. This data is sent to the server as input and analyzed in real time. The server uses the data to determine the baby's condition. Specifically, video and audio of when the baby starts crying are sent to the server, and the server determines whether the baby is awake or not.

[0079] Step 5:

[0080] The server analyzes the monitoring data to confirm that the baby has fallen asleep and sends a notification to the user. The input is the monitoring data, and the output is a notification sent to the smartphone saying "The baby has fallen asleep." Once the server finishes its analysis and detects sleep, a notification is displayed on the user's smartphone.

[0081] Step 6:

[0082] The server adjusts the room temperature based on temperature sensor data. The server receives temperature data from the terminal and controls air conditioners and other devices as needed. Input is temperature sensor data, and output is an update of the temperature setting. If the server determines that the room temperature is outside the optimal range, the air conditioner's set temperature is automatically adjusted.

[0083] Step 7:

[0084] The server sends alerts to the user if any abnormalities occur in the baby or the surrounding environment. The server constantly monitors and checks environmental data to detect anomalies. Inputs are sensor data indicating abnormalities, and outputs are warning notifications such as "Body temperature is rising." If the baby's body temperature exceeds the set threshold, the server quickly sends a warning message to the user's smartphone.

[0085] (Application Example 1)

[0086] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0087] In modern childcare environments, a significant problem is the amount of time and effort parents spend getting their babies to sleep and maintaining their health. Furthermore, manual adjustments and monitoring are necessary to ensure the baby's safety and a comfortable sleep environment. To address these challenges, automated systems are needed.

[0088] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0089] In this invention, the server includes means for generating optimal music to lull the baby to sleep, monitoring means equipped with a camera and sound device for monitoring the baby's condition, and adjustment means for measuring and adjusting the baby's body temperature and room temperature. This makes it possible to automatically maintain a comfortable sleeping environment for the baby without parental intervention.

[0090] The "generation means" refers to a device that has the function of generating music that is optimal for putting a baby to sleep.

[0091] "Monitoring equipment" refers to devices that have the function of using a camera and an audio device to monitor the baby's condition.

[0092] A "regulating device" is a device that measures the baby's body temperature and room temperature and adjusts the environment based on those measurements.

[0093] The "analysis means" is a device that analyzes the baby's condition data and feeds the results back into music generation.

[0094] A "means of communication" refers to a system that notifies parents or caregivers when the baby falls asleep.

[0095] An "alert system" is a device that provides a warning when an anomaly is detected.

[0096] An "environmental control means" is a device that controls the air conditioning system based on environmental information to provide a comfortable environment for the baby.

[0097] "Audio output means" refers to a device that has the function of outputting generated music from an audio device.

[0098] A "reporting means" is a device that records the baby's condition, analyzes the patterns, and provides information to the user.

[0099] The system implementing this invention integrates multiple means to support the comfortable sleep and safety of babies. The server is responsible for processing data in real time at all times and taking necessary actions.

[0100] The server uses a generation mechanism to create the optimal lullaby based on the baby's preferred music type and past data, utilizing a generation AI model. This process employs machine learning algorithms using Python and Tensorflow®. The generated music is played around the baby through speakers via an audio output mechanism.

[0101] As a monitoring method, a camera and audio device attached to the terminal monitor the baby's condition and transmit the data to a server. OpenCV is used to process the video data and analyze the baby's movements and sounds.

[0102] The adjustment mechanism automatically adjusts the room temperature via the air conditioning system based on data from temperature sensors. The server analyzes environmental and body temperature data collected using Firebase and makes appropriate settings.

[0103] Furthermore, the analysis system analyzes the baby's sleep data and provides feedback to the music generation system based on the results. This allows the accuracy of the generation system to improve over time.

[0104] As a means of communication, a notification will be sent to the user when it is determined that the baby has fallen asleep. This function will be implemented using a combination of Flask and a REST API.

[0105] The alert system immediately sends a warning to the user if the baby's body temperature exceeds a certain threshold or if any abnormality is detected.

[0106] As a concrete example, the generative AI model uses the following prompt: "Baby's basic information: 3 months old, preferred music type: classical. Please generate the best lullaby."

[0107] This system allows parents to entrust their baby's sleep environment to someone else with peace of mind, reducing the burden of childcare.

[0108] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0109] Step 1:

[0110] The user launches a smartphone app and enters basic information about their baby and their preferred music type. This information is sent to a server, where an AI model generates prompt messages. Based on the entered data, the server uses a generation tool to prepare to create the most suitable lullaby.

[0111] Step 2:

[0112] The server uses a generative AI model to generate lullabies based on prompt text. Using Python and TensorFlow, it analyzes historical data and trends to select the most suitable music. The generated lullaby is sent to a speaker via an audio output device. In this step, prompt text and historical data are used as input, and music data is obtained as output.

[0113] Step 3:

[0114] A device equipped with a camera and microphone monitors the baby's condition and collects audio and video data. The device uses OpenCV to analyze the video and audio and transmits the data to a server in real time. The input is video and audio data, and the output is the analyzed information about the baby's condition.

[0115] Step 4:

[0116] The server uses a control mechanism to receive data from the temperature sensor and issues instructions to control the air conditioner. It analyzes the body temperature and room temperature data collected via Firebase to maintain the room temperature at an optimal level for the baby. In this step, temperature data is used as input and air conditioner setting information is obtained as output.

[0117] Step 5:

[0118] The server determines the baby's sleep state. When the server determines that the baby has "fallen asleep," it sends a notification to the user via a communication method. If an abnormality is detected, it uses an alert method to immediately send a warning to the user. The input is the baby's status data, and the output is notification or warning information.

[0119] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0120] The present invention introduces a novel approach to the system that recognizes the user's emotions and utilizes them to help the baby fall asleep. The user operates the system using a smartphone application, providing information about getting the baby to sleep while simultaneously recording their own emotional state.

[0121] The device is equipped with an emotion engine that analyzes the user's emotions from their face and voice. It uses facial recognition and voice analysis technologies to recognize the user's emotions and sends that data to a server. This allows the user's stress level and relaxation level to be evaluated in real time.

[0122] The server integrates emotional data and baby status data to generate the most appropriate lullaby. This generation method adjusts the tempo and tone of the music, taking into account data from the emotional engine, and selects music that also helps the parent relax. In this way, a system is created in which the user's emotional state indirectly influences the baby's comfort.

[0123] As a monitoring tool, the camera and microphone installed in the device continuously monitor the baby's movements and cries, and transmit this information to a server. The analysis tool analyzes this data to determine if the baby's sleep has improved, and uses this information to improve future music generation.

[0124] Furthermore, the server uses notification and warning mechanisms to inform the user when it determines that the baby has fallen asleep or when an abnormality occurs. For example, if it determines that the user is experiencing stress, the notification mechanism can offer suggestions for relaxation.

[0125] For example, if the user is feeling sleepy, the emotion engine detects this and generates and plays relaxing classical music. Furthermore, if the user is feeling stressed, the tempo of the music can be adjusted to create a calmer atmosphere. In this way, the system of the present invention provides an integrated sleep environment that focuses on both the baby and the parent.

[0126] The following describes the processing flow.

[0127] Step 1:

[0128] The user launches the smartphone app and enters information about the baby (age, health, etc.). To enable emotion recognition, the user points their face at the camera and starts the app.

[0129] Step 2:

[0130] The device uses its camera and microphone to analyze the user's facial expressions and voice tone, and an emotion engine determines the user's emotional state. This data is then transmitted to the server in real time.

[0131] Step 3:

[0132] The server combines the received emotional data with previously accumulated data and uses an AI algorithm to generate the optimal lullaby. Music genre, tempo, volume, and other elements are adjusted according to the user's emotions.

[0133] Step 4:

[0134] The generated lullaby data is sent to the device. The device plays the music through its speaker, creating an environment that helps soothe the baby to sleep.

[0135] Step 5:

[0136] The device continues to monitor the baby using its camera and microphone, sending its movements and cries to the server. This allows for real-time monitoring of the situation.

[0137] Step 6:

[0138] The server analyzes both the baby's data and emotional data simultaneously, and evaluates the integrated daily data using analytical tools. It then provides feedback on particularly effective moments, which are used to improve future music generation.

[0139] Step 7:

[0140] Once the server confirms that the baby has fallen asleep, it sends a notification to the user via the device. It can also offer relaxation suggestions based on the user's emotions. If an anomaly is detected, it immediately sends an alert.

[0141] (Example 2)

[0142] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0143] There is a lack of effective lullabies and sleep training methods that take into account the impact of parents' emotional state on the baby's sleep environment. Traditional systems focus only on the baby's condition and do not fully utilize how parental stress levels and relaxation can help in getting the baby to sleep.

[0144] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0145] In this invention, the server includes an emotion analysis means, a music generation means, and a suggestion means. This makes it possible to analyze the user's emotional state in real time, generate music based on that analysis, and further make suggestions to the user to promote relaxation.

[0146] "Emotional analysis means" refers to a device that analyzes a user's facial expressions and voice to understand the user's emotional state.

[0147] "Music generation means" refers to a device or technology for generating music that is appropriate for the baby's condition or the user's emotions, based on acquired data.

[0148] The "integration means" is a device that integrates user emotion data and baby situation data and generates prompt sentences suitable for the generation AI model.

[0149] A "generative AI model" is an artificial intelligence model that generates new data or content based on specific prompt sentences.

[0150] "Observation methods" refer to devices such as cameras and microphones used to monitor the baby's movements and sounds and collect data.

[0151] A "notification mechanism" is a system that informs the user when the baby has fallen asleep.

[0152] "Suggestion methods" refer to devices and technologies used to offer suggestions to users that promote relaxation.

[0153] A "warning mechanism" is a mechanism that issues a warning to the user when the system detects an anomaly.

[0154] To implement this invention, the user needs to input information about getting the baby to sleep and record their own emotional state by operating a smartphone application. The user's facial expressions and voice are captured and analyzed in real time by an emotion analysis device via the smartphone.

[0155] The device uses facial recognition and voice analysis technologies to acquire user emotion data. This data is sent to a server and integrated with the baby's status data. The integration mechanism generates prompt statements for the AI ​​model to process based on this data.

[0156] The server uses a music generation system to create music optimized for the baby and parent based on prompt messages and emotional data. The tempo and tone of the music are adjusted according to the baby's condition and the parent's emotions. For example, a prompt message might say, "Generate music that promotes relaxation."

[0157] In this system, the terminal uses a camera and microphone as observation tools to continuously monitor the baby's movements and cries. This data is sent to a server where the baby's sleep patterns are analyzed in detail.

[0158] The server notifies the user via a notification system if an anomaly is detected or if it determines that the baby has fallen asleep. Furthermore, if the user's stress level is detected, the system can send suggestions to encourage relaxation. In this way, the system provides a sleep environment that prioritizes the comfort of both the baby and the parent.

[0159] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0160] Step 1:

[0161] The user launches a smartphone application and selects the lullaby mode. The input here consists of the user's selection and real-time data of facial expressions and voice. The device acquires this data using its camera and microphone and performs emotion analysis. Specifically, the device uses facial recognition and voice analysis technologies to determine the user's emotional state.

[0162] Step 2:

[0163] The terminal sends the results of its emotion analysis to the server. The input data sent is the user's emotional state data. The server receives this input and integrates it with other information about getting the baby to sleep. The data processing here involves combining and integrating the emotion data and the baby's situation data to generate prompt messages.

[0164] Step 3:

[0165] The server sends the generated prompt text to the generation AI model, instructing it to generate the most suitable music. The input at this stage consists of the prompt text and integrated emotional and situational data. The generation AI model receives this data and uses a music generation algorithm to output an appropriate lullaby. The generated music is adjusted in tempo and tone to suit the user and the baby's state.

[0166] Step 4:

[0167] The device plays the generated music. The input here is the music data output from the generation AI model. Specifically, the device plays the music through the speaker and adjusts the volume and playback timing.

[0168] Step 5:

[0169] The device continues to monitor the baby's movements and cries using its camera and microphone, and sends this data to the server. The monitoring input consists of the baby's movements and audio data. The server receives this data and evaluates the baby's sleep state. If the baby's condition improves, it generates feedback to be used for future music generation.

[0170] Step 6:

[0171] The server sends notifications and warnings to the user when the baby falls asleep or when it detects an abnormality. The input here is the baby's sleep evaluation data, and the output is the content of the notification to the user. Specifically, the server displays a notification on the user's smartphone and makes suggestions based on the situation.

[0172] (Application Example 2)

[0173] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0174] When getting a baby to sleep, parental fatigue and stress can be a major problem, increasing the burden of childcare. Furthermore, a parent's emotional state can directly affect a baby's calmness and sleep. Therefore, there is a need for effective childcare support systems that consider the well-being of both parents and babies.

[0175] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0176] In this invention, the server includes a generation means for generating music optimal for putting a baby to sleep, an emotion analysis and suggestion means for analyzing the user's emotions and providing advice and suggestions to encourage relaxation in the parent, and a commercial support means for providing childcare-related support based on the parent's emotional state within the store. This makes it possible to provide childcare support that takes the parent's emotional state into consideration, and to provide a comfortable environment for both the parent and the baby.

[0177] "Generating means" refers to a device or method that has the function of generating music that is optimal for putting a baby to sleep.

[0178] "Monitoring means" refers to devices or methods that use imaging devices and sound collection devices to monitor the condition of a baby.

[0179] "Environmental adjustment means" refers to devices or methods for measuring and appropriately controlling a baby's body temperature and room temperature.

[0180] "Analysis means" refers to devices or methods that analyze data from when a baby falls asleep and use that data to generate music.

[0181] "Means of communication" refers to devices or methods for providing appropriate notifications when a baby falls asleep.

[0182] A "warning mechanism" refers to a device or method used to issue a warning when an abnormality is detected.

[0183] "Emotional analysis and suggestion means" refers to a device or method for analyzing a user's emotions and providing advice or suggestions to parents to promote relaxation.

[0184] "Commercial support measures" refer to devices or methods for providing childcare-related support based on the emotional state of parents within a store.

[0185] The system of the present invention consists of a terminal, a server, and a user.

[0186] The device is equipped with an imaging device and an audio collection device, and its role is to collect and analyze the emotions of the baby and parent in real time. This analysis uses an emotion engine to analyze the user's emotional state using video data obtained from the camera and audio data collected from the microphone. For example, if the user is feeling stressed, the analysis results are sent to the server.

[0187] The server performs computational processing to optimize childcare support based on the received emotional data and child state data. To generate appropriate music using a generation method, a machine learning model is used to create music that takes into account past data and the parent's emotional state. This generated music not only helps babies relax and fall asleep, but also helps parents relax.

[0188] The server also provides advice and suggestions to help parents relax based on their condition. For example, if it detects that a parent is tired in the store, it can guide them to "please use the relaxation area in the store."

[0189] As an example of a prompt, using a prompt in the format of "Based on this user's emotional state, please provide the best parenting advice" allows the generative AI model to provide appropriate support information.

[0190] In this way, the system of the present invention is intended to provide an integrated childcare support environment that focuses on both parents and babies.

[0191] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0192] Step 1:

[0193] The device uses an imaging device and a voice acquisition device to collect data on the user and the baby in real time. It receives video data from the camera and audio data from the microphone as input. Using this data, an emotion engine analyzes facial expressions and voice tone to identify the user's emotional state. It generates emotional state data as output and provides it for the next step.

[0194] Step 2:

[0195] The terminal sends the emotional state data obtained in Step 1 to the server. It uses the emotional state data as input and transmits it to the server via the internet. After receiving the emotional data, the server stores it in its database and prepares to proceed to the next step. The output confirms that the data has been successfully saved to the server.

[0196] Step 3:

[0197] The server generates music for childcare support based on emotional state data and baby status data. It uses emotional state data and historical data such as the baby's sleep patterns as input. A generation AI model optimizes the music's tempo and melody to create lullabies that soothe both the user and the baby. The generated music data is then sent back to the device as output.

[0198] Step 4:

[0199] The device receives music data from the server and plays it through its speakers. It receives music data as input and uses an audio output interface to allow the user and the baby to listen. It adjusts the volume and playback timing to create a more relaxing environment for the user. It then plays the music into the environment as output.

[0200] Step 5:

[0201] The server continues to monitor emotional state data and the baby's condition, repeating the process in step 3 whenever new data becomes available. It receives real-time emotional and sleep data as input and updates the output with the most suitable lullabies and parenting advice at that moment. This ensures that appropriate support is always provided according to the user's and baby's condition.

[0202] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0203] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0204] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0205] [Second Embodiment]

[0206] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0207] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0208] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0209] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0210] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0211] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0212] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0213] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0214] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0215] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0216] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0217] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0218] The system of this invention integrates functions to assist in getting babies to sleep. Users can operate this system through a smartphone app. When the app is launched, the user enters the baby's basic information and preferred music type, and then begins the sleep-inducing process.

[0219] The server uses an AI algorithm to generate the most suitable lullaby for the baby based on user input data. This generation method analyzes past data and trends to select the most effective music. The generated lullaby is played through a speaker via the device.

[0220] The device monitors the baby's condition using a camera and microphone, and transmits the data to the server in real time. Sensors, acting as monitoring tools, detect the baby's movements and sounds, and check their status. The server analyzes this data to determine the baby's sleep state and provides feedback as needed.

[0221] Furthermore, thermography and temperature sensors monitor the baby's body temperature and room temperature. The control system adjusts air conditioning and other settings appropriately based on the temperature data to create a comfortable environment for the baby.

[0222] The server notifies the user via the device when it determines that the baby has fallen asleep. It also has a function to immediately send an alert if an abnormality is detected. For example, if the baby's body temperature exceeds a set threshold, the server can issue an alert and notify the user's device.

[0223] This system configuration automates the entire process of getting a baby to sleep, reducing the burden on parents while ensuring the baby's safety.

[0224] The following describes the processing flow.

[0225] Step 1:

[0226] The user launches the app on their smartphone and enters basic information about their baby (age, music preferences, etc.). This information is then sent from the app to the server.

[0227] Step 2:

[0228] The server uses an AI algorithm to generate the optimal lullaby based on the information received from the user. This lullaby is selected considering past success data and current trends.

[0229] Step 3:

[0230] The generated lullaby is sent from the server to the terminal. The terminal plays this music through its speakers, creating an environment that helps soothe the baby to sleep.

[0231] Step 4:

[0232] The device monitors the baby's condition using a camera and microphone and transmits the data to a server in real time. The monitoring method involves detecting the baby's movements and sounds.

[0233] Step 5:

[0234] The server analyzes the video and audio data sent from the terminal to determine the baby's sleep state. If necessary, it regenerates an appropriate lullaby.

[0235] Step 6:

[0236] Furthermore, a temperature sensor built into the device monitors the baby's body temperature and the room temperature. Based on this data, the server adjusts the air conditioner settings to maintain a comfortable environment.

[0237] Step 7:

[0238] The server sends a notification to the user via the device when it determines that the baby has fallen asleep safely. It also immediately sends an alert to the user if any abnormalities (such as a high fever or prolonged crying) are detected.

[0239] (Example 1)

[0240] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0241] In today's busy lifestyle, efficiently getting babies to sleep is a crucial challenge for caregivers. Traditional methods make it difficult to accurately assess a baby's condition and maintain an appropriate environment, placing a heavy burden on caregivers. Furthermore, there is a need for a way to respond quickly to any health problems in babies, but existing systems are insufficient to address this.

[0242] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0243] In this invention, the server includes a generation means for generating optimal music to soothe a baby to sleep, a monitoring means equipped with a video recording device and an audio acquisition device for monitoring the baby's condition, and an environmental adjustment means for measuring and controlling the baby's body temperature and room temperature. This makes it possible to reduce the burden on caregivers and ensure safe and comfortable sleep for babies by providing appropriate music and environmental adjustments while monitoring the baby's condition in real time.

[0244] "Generation method" refers to the function or technology that generates optimal music for putting babies to sleep. This includes processes that automatically generate music using AI models and data analysis technologies.

[0245] "Monitoring means" refers to a mechanism equipped with a video recording device and an audio acquisition device used to monitor the baby's condition. This allows for real-time observation of the baby's behavior and sounds.

[0246] "Environmental adjustment means" refers to a mechanism for measuring the baby's body temperature and room temperature and controlling them as needed. Specifically, this includes functions that maintain an appropriate indoor environment by operating thermosensors, air conditioners, etc.

[0247] "Information processing means" refers to a function that analyzes data from the time the baby falls asleep and feeds the results back into music generation. This includes a process that uses data analysis technology to enhance the effectiveness of music generation.

[0248] "Notification means" refers to a function that notifies the user when the baby falls asleep. Specifically, this includes sending alerts and notifications to smartphones and other devices.

[0249] "Alarming mechanisms" refer to functions that issue warnings when an abnormality is detected. This includes issuing alerts to quickly inform the user of any abnormalities in the baby's health or environment.

[0250] This invention is a system for effectively getting babies to sleep, combining AI-powered music generation with real-time monitoring. This system primarily operates through the collaboration of a server, terminals, and users.

[0251] The server uses a generative AI model to generate music best suited for babies. Users input basic information about their baby and their musical preferences through a smartphone app, and this data is sent to the server. The server analyzes past data and trends and automatically generates music based on this analysis. For example, if a user requests "relaxing piano music," the generative AI model will be prompted with the command, "Generate a soothing piano lullaby for babies."

[0252] Meanwhile, the device plays a role in monitoring the baby's condition. Equipped with a camera and microphone, the device monitors the baby's behavior and sends the data to a server. The server analyzes this data to determine the baby's sleep state and any abnormalities.

[0253] Furthermore, the server measures temperature and humidity and controls air conditioning and other appliances to properly manage the environment around the baby. Once the user sets the environmental conditions, the device's sensors measure the indoor environment, and the server automatically adjusts the settings after analysis.

[0254] These features allow users to help their babies sleep safely and comfortably, reducing the burden of childcare.

[0255] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0256] Step 1:

[0257] The user launches the smartphone app and enters the baby's basic information (name, age, favorite music genre). The entered data is sent to the server. This allows the server to obtain basic data for music generation based on the information received from the user. Specifically, if the user selects "classical music," this selection is passed from the smartphone to the server.

[0258] Step 2:

[0259] The server uses a generative AI model to generate music best suited for a baby, based on data from the user. Input includes the user's music genre selection and the baby's age, while output is a music file generated by the AI ​​model. For example, the prompt "Generate relaxing classical music" is input to the model, and the generated music data is output. Specifically, the AI ​​composes the music in the cloud, and the generated file is saved on the server.

[0260] Step 3:

[0261] The server sends the generated music to the device. The device receives this music and plays it through a speaker in the room where the baby is. The input here is music data from the AI ​​model, and the output is the sound of the music being played. The music starts playing from the device's speaker, and the volume and playback time follow conditions set by the user beforehand.

[0262] Step 4:

[0263] The device sends data from its camera and microphone to a server to monitor the baby's condition. This monitoring data includes the baby's movements and sounds. This data is sent to the server as input and analyzed in real time. The server uses the data to determine the baby's condition. Specifically, video and audio of when the baby starts crying are sent to the server, and the server determines whether the baby is awake or not.

[0264] Step 5:

[0265] The server analyzes the monitoring data to confirm that the baby has fallen asleep and sends a notification to the user. The input is the monitoring data, and the output is a notification sent to the smartphone saying "The baby has fallen asleep." Once the server finishes its analysis and detects sleep, a notification is displayed on the user's smartphone.

[0266] Step 6:

[0267] The server adjusts the room temperature based on temperature sensor data. The server receives temperature data from the terminal and controls air conditioners and other devices as needed. Input is temperature sensor data, and output is an update of the temperature setting. If the server determines that the room temperature is outside the optimal range, the air conditioner's set temperature is automatically adjusted.

[0268] Step 7:

[0269] The server sends alerts to the user if any abnormalities occur in the baby or the surrounding environment. The server constantly monitors and checks environmental data to detect anomalies. Inputs are sensor data indicating abnormalities, and outputs are warning notifications such as "Body temperature is rising." If the baby's body temperature exceeds the set threshold, the server quickly sends a warning message to the user's smartphone.

[0270] (Application Example 1)

[0271] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0272] In modern childcare environments, a significant problem is the amount of time and effort parents spend getting their babies to sleep and maintaining their health. Furthermore, manual adjustments and monitoring are necessary to ensure the baby's safety and a comfortable sleep environment. To address these challenges, automated systems are needed.

[0273] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0274] In this invention, the server includes means for generating optimal music to lull the baby to sleep, monitoring means equipped with a camera and sound device for monitoring the baby's condition, and adjustment means for measuring and adjusting the baby's body temperature and room temperature. This makes it possible to automatically maintain a comfortable sleeping environment for the baby without parental intervention.

[0275] The "generation means" refers to a device that has the function of generating music that is optimal for putting a baby to sleep.

[0276] "Monitoring equipment" refers to devices that have the function of using a camera and an audio device to monitor the baby's condition.

[0277] A "regulating device" is a device that measures the baby's body temperature and room temperature and adjusts the environment based on those measurements.

[0278] The "analysis means" is a device that analyzes the baby's condition data and feeds the results back into music generation.

[0279] A "means of communication" refers to a system that notifies parents or caregivers when the baby falls asleep.

[0280] An "alert system" is a device that provides a warning when an anomaly is detected.

[0281] The "environmental control means" has the function of controlling the air conditioner based on environmental information to provide a comfortable environment for the baby.

[0282] The "acoustic output means" has the function of outputting the generated music from the audio device.

[0283] The "report providing means" has the function of recording the baby's state, analyzing the pattern, and providing information to the user.

[0284] The system for implementing this invention integrates multiple means to support the baby's comfortable sleep and safety. The server is always responsible for processing data in real time and performing necessary actions.

[0285] The server uses the generation means to generate an optimal lullaby by utilizing the generated AI model based on the baby's preferred music type and previous data. Machine learning algorithms such as Python and TensorFlow are used in this process. The generated music is played around the baby from the speaker through the acoustic output means.

[0286] As monitoring means, the photographing device and the acoustic device attached to the terminal monitor the baby's condition and send the data to the server. The video data is processed using OpenCV to analyze the baby's movements and voices.

[0287] The adjustment means automatically adjusts the room temperature through the air conditioner based on the data from the temperature sensor. The server analyzes the environmental data and body temperature data collected using Firebase and makes appropriate settings.

[0288] Also, the analysis means analyzes the baby's sleep data and provides feedback for music generation based on the results. As a result, the accuracy of the generation means improves over time.

[0289] As a means of communication, a notification will be sent to the user when it is determined that the baby has fallen asleep. This function will be implemented using a combination of Flask and a REST API.

[0290] The alert system immediately sends a warning to the user if the baby's body temperature exceeds a certain threshold or if any abnormality is detected.

[0291] As a concrete example, the generative AI model uses the following prompt: "Baby's basic information: 3 months old, preferred music type: classical. Please generate the best lullaby."

[0292] This system allows parents to entrust their baby's sleep environment to someone else with peace of mind, reducing the burden of childcare.

[0293] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0294] Step 1:

[0295] The user launches a smartphone app and enters basic information about their baby and their preferred music type. This information is sent to a server, where an AI model generates prompt messages. Based on the entered data, the server uses a generation tool to prepare to create the most suitable lullaby.

[0296] Step 2:

[0297] The server uses a generative AI model to generate lullabies based on prompt text. Using Python and TensorFlow, it analyzes historical data and trends to select the most suitable music. The generated lullaby is sent to a speaker via an audio output device. In this step, prompt text and historical data are used as input, and music data is obtained as output.

[0298] Step 3:

[0299] A device equipped with a camera and microphone monitors the baby's condition and collects audio and video data. The device uses OpenCV to analyze the video and audio and transmits the data to a server in real time. The input is video and audio data, and the output is the analyzed information about the baby's condition.

[0300] Step 4:

[0301] The server uses a control mechanism to receive data from the temperature sensor and issues instructions to control the air conditioner. It analyzes the body temperature and room temperature data collected via Firebase to maintain the room temperature at an optimal level for the baby. In this step, temperature data is used as input and air conditioner setting information is obtained as output.

[0302] Step 5:

[0303] The server determines the baby's sleep state. When the server determines that the baby has "fallen asleep," it sends a notification to the user via a communication method. If an abnormality is detected, it uses an alert method to immediately send a warning to the user. The input is the baby's status data, and the output is notification or warning information.

[0304] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0305] The present invention introduces a novel approach to the system that recognizes the user's emotions and utilizes them to help the baby fall asleep. The user operates the system using a smartphone application, providing information about getting the baby to sleep while simultaneously recording their own emotional state.

[0306] The terminal is equipped with an emotion engine for analyzing emotions from the user's face, voice, etc. It uses face recognition technology and voice analysis technology to recognize the user's emotions and transmit the data to the server. As a result, the user's stress level and relaxation degree are evaluated in real time.

[0307] The server integrates the emotion data and the baby's situation data to generate the most appropriate lullaby. By considering the data from the emotion engine, this generation means adjusts the tempo and tone of the music and selects music that allows the parent to relax as well. In this way, a mechanism is constructed in which the user's emotional state indirectly affects the comfort of the baby.

[0308] The camera and microphone installed on the terminal as monitoring means continuously monitor the baby's movements and crying sounds and transmit the information to the server. The analysis means analyzes these data, determines whether the baby's sleep state has improved, and provides feedback for future music generation.

[0309] In addition, when the server determines that the baby has fallen asleep or when an abnormality occurs, it uses the notification and warning means to inform the user. For example, when it is determined that the user is feeling stressed, the notification means can also make a proposal for relaxation.

[0310] As a specific example, when the user is feeling sleepy, the emotion engine detects this and generates and plays relaxing classical music. Also, when the user is feeling stressed, the tempo of the music can be adjusted to create a more soothing atmosphere. In this way, the system of the present invention provides an integrated bedtime environment that focuses on both the baby and the parent.

[0311] The following describes the processing flow.

[0312] Step 1:

[0313] The user launches the smartphone app and enters information about the baby (age, health, etc.). To enable emotion recognition, the user points their face at the camera and starts the app.

[0314] Step 2:

[0315] The device uses its camera and microphone to analyze the user's facial expressions and voice tone, and an emotion engine determines the user's emotional state. This data is then transmitted to the server in real time.

[0316] Step 3:

[0317] The server combines the received emotional data with previously accumulated data and uses an AI algorithm to generate the optimal lullaby. Music genre, tempo, volume, and other elements are adjusted according to the user's emotions.

[0318] Step 4:

[0319] The generated lullaby data is sent to the device. The device plays the music through its speaker, creating an environment that helps soothe the baby to sleep.

[0320] Step 5:

[0321] The device continues to monitor the baby using its camera and microphone, sending its movements and cries to the server. This allows for real-time monitoring of the situation.

[0322] Step 6:

[0323] The server analyzes both the baby's data and emotional data simultaneously, and evaluates the integrated daily data using analytical tools. It then provides feedback on particularly effective moments, which are used to improve future music generation.

[0324] Step 7:

[0325] Once the server confirms that the baby has fallen asleep, it sends a notification to the user via the device. It can also offer relaxation suggestions based on the user's emotions. If an anomaly is detected, it immediately sends an alert.

[0326] (Example 2)

[0327] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0328] There is a lack of effective lullabies and sleep training methods that take into account the impact of parents' emotional state on the baby's sleep environment. Traditional systems focus only on the baby's condition and do not fully utilize how parental stress levels and relaxation can help in getting the baby to sleep.

[0329] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0330] In this invention, the server includes an emotion analysis means, a music generation means, and a suggestion means. This makes it possible to analyze the user's emotional state in real time, generate music based on that analysis, and further make suggestions to the user to promote relaxation.

[0331] "Emotional analysis means" refers to a device that analyzes a user's facial expressions and voice to understand the user's emotional state.

[0332] "Music generation means" refers to a device or technology for generating music that is appropriate for the baby's condition or the user's emotions, based on acquired data.

[0333] The "integration means" is a device that integrates user emotion data and baby situation data and generates prompt sentences suitable for the generation AI model.

[0334] A "generative AI model" is an artificial intelligence model that generates new data or content based on specific prompt sentences.

[0335] "Observation methods" refer to devices such as cameras and microphones used to monitor the baby's movements and sounds and collect data.

[0336] A "notification mechanism" is a system that informs the user when the baby has fallen asleep.

[0337] "Suggestion methods" refer to devices and technologies used to offer suggestions to users that promote relaxation.

[0338] A "warning mechanism" is a mechanism that issues a warning to the user when the system detects an anomaly.

[0339] To implement this invention, the user needs to input information about getting the baby to sleep and record their own emotional state by operating a smartphone application. The user's facial expressions and voice are captured and analyzed in real time by an emotion analysis device via the smartphone.

[0340] The device uses facial recognition and voice analysis technologies to acquire user emotion data. This data is sent to a server and integrated with the baby's status data. The integration mechanism generates prompt statements for the AI ​​model to process based on this data.

[0341] The server uses a music generation system to create music optimized for the baby and parent based on prompt messages and emotional data. The tempo and tone of the music are adjusted according to the baby's condition and the parent's emotions. For example, a prompt message might say, "Generate music that promotes relaxation."

[0342] In this system, the terminal uses a camera and microphone as observation tools to continuously monitor the baby's movements and cries. This data is sent to a server where the baby's sleep patterns are analyzed in detail.

[0343] The server notifies the user via a notification system if an anomaly is detected or if it determines that the baby has fallen asleep. Furthermore, if the user's stress level is detected, the system can send suggestions to encourage relaxation. In this way, the system provides a sleep environment that prioritizes the comfort of both the baby and the parent.

[0344] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0345] Step 1:

[0346] The user launches a smartphone application and selects the lullaby mode. The input here consists of the user's selection and real-time data of facial expressions and voice. The device acquires this data using its camera and microphone and performs emotion analysis. Specifically, the device uses facial recognition and voice analysis technologies to determine the user's emotional state.

[0347] Step 2:

[0348] The terminal sends the results of its emotion analysis to the server. The input data sent is the user's emotional state data. The server receives this input and integrates it with other information about getting the baby to sleep. The data processing here involves combining and integrating the emotion data and the baby's situation data to generate prompt messages.

[0349] Step 3:

[0350] The server sends the generated prompt text to the generation AI model, instructing it to generate the most suitable music. The input at this stage consists of the prompt text and integrated emotional and situational data. The generation AI model receives this data and uses a music generation algorithm to output an appropriate lullaby. The generated music is adjusted in tempo and tone to suit the user and the baby's state.

[0351] Step 4:

[0352] The device plays the generated music. The input here is the music data output from the generation AI model. Specifically, the device plays the music through the speaker and adjusts the volume and playback timing.

[0353] Step 5:

[0354] The device continues to monitor the baby's movements and cries using its camera and microphone, and sends this data to the server. The monitoring input consists of the baby's movements and audio data. The server receives this data and evaluates the baby's sleep state. If the baby's condition improves, it generates feedback to be used for future music generation.

[0355] Step 6:

[0356] The server sends notifications and warnings to the user when the baby falls asleep or when it detects an abnormality. The input here is the baby's sleep evaluation data, and the output is the content of the notification to the user. Specifically, the server displays a notification on the user's smartphone and makes suggestions based on the situation.

[0357] (Application Example 2)

[0358] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0359] When getting a baby to sleep, parental fatigue and stress can be a major problem, increasing the burden of childcare. Furthermore, a parent's emotional state can directly affect a baby's calmness and sleep. Therefore, there is a need for effective childcare support systems that consider the well-being of both parents and babies.

[0360] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0361] In this invention, the server includes a generation means for generating music optimal for putting a baby to sleep, an emotion analysis and suggestion means for analyzing the user's emotions and providing advice and suggestions to encourage relaxation in the parent, and a commercial support means for providing childcare-related support based on the parent's emotional state within the store. This makes it possible to provide childcare support that takes the parent's emotional state into consideration, and to provide a comfortable environment for both the parent and the baby.

[0362] "Generating means" refers to a device or method that has the function of generating music that is optimal for putting a baby to sleep.

[0363] "Monitoring means" refers to devices or methods that use imaging devices and sound collection devices to monitor the condition of a baby.

[0364] "Environmental adjustment means" refers to devices or methods for measuring and appropriately controlling a baby's body temperature and room temperature.

[0365] "Analysis means" refers to devices or methods that analyze data from when a baby falls asleep and use that data to generate music.

[0366] "Means of communication" refers to devices or methods for providing appropriate notifications when a baby falls asleep.

[0367] A "warning mechanism" refers to a device or method used to issue a warning when an abnormality is detected.

[0368] "Emotional analysis and suggestion means" refers to a device or method for analyzing a user's emotions and providing advice or suggestions to parents to promote relaxation.

[0369] "Commercial support measures" refer to devices or methods for providing childcare-related support based on the emotional state of parents within a store.

[0370] The system of the present invention consists of a terminal, a server, and a user.

[0371] The device is equipped with an imaging device and an audio collection device, and its role is to collect and analyze the emotions of the baby and parent in real time. This analysis uses an emotion engine to analyze the user's emotional state using video data obtained from the camera and audio data collected from the microphone. For example, if the user is feeling stressed, the analysis results are sent to the server.

[0372] The server performs computational processing to optimize childcare support based on the received emotional data and child state data. To generate appropriate music using a generation method, a machine learning model is used to create music that takes into account past data and the parent's emotional state. This generated music not only helps babies relax and fall asleep, but also helps parents relax.

[0373] The server also provides advice and suggestions to help parents relax based on their condition. For example, if it detects that a parent is tired in the store, it can guide them to "please use the relaxation area in the store."

[0374] As an example of a prompt, using a prompt in the format of "Based on this user's emotional state, please provide the best parenting advice" allows the generative AI model to provide appropriate support information.

[0375] In this way, the system of the present invention is intended to provide an integrated childcare support environment that focuses on both parents and babies.

[0376] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0377] Step 1:

[0378] The device uses an imaging device and a voice acquisition device to collect data on the user and the baby in real time. It receives video data from the camera and audio data from the microphone as input. Using this data, an emotion engine analyzes facial expressions and voice tone to identify the user's emotional state. It generates emotional state data as output and provides it for the next step.

[0379] Step 2:

[0380] The terminal sends the emotional state data obtained in Step 1 to the server. It uses the emotional state data as input and transmits it to the server via the internet. After receiving the emotional data, the server stores it in its database and prepares to proceed to the next step. The output confirms that the data has been successfully saved to the server.

[0381] Step 3:

[0382] The server generates music for childcare support based on emotional state data and baby status data. It uses emotional state data and historical data such as the baby's sleep patterns as input. A generation AI model optimizes the music's tempo and melody to create lullabies that soothe both the user and the baby. The generated music data is then sent back to the device as output.

[0383] Step 4:

[0384] The device receives music data from the server and plays it through its speakers. It receives music data as input and uses an audio output interface to allow the user and the baby to listen. It adjusts the volume and playback timing to create a more relaxing environment for the user. It then plays the music into the environment as output.

[0385] Step 5:

[0386] The server continues to monitor emotional state data and the baby's condition, repeating the process in step 3 whenever new data becomes available. It receives real-time emotional and sleep data as input and updates the output with the most suitable lullabies and parenting advice at that moment. This ensures that appropriate support is always provided according to the user's and baby's condition.

[0387] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0388] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0389] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0390] [Third Embodiment]

[0391] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0392] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0393] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0394] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0395] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0396] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0397] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0398] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0399] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0400] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0401] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0402] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0403] The system of this invention integrates functions to assist in getting babies to sleep. Users can operate this system through a smartphone app. When the app is launched, the user enters the baby's basic information and preferred music type, and then begins the sleep-inducing process.

[0404] The server uses an AI algorithm to generate the most suitable lullaby for the baby based on user input data. This generation method analyzes past data and trends to select the most effective music. The generated lullaby is played through a speaker via the device.

[0405] The device monitors the baby's condition using a camera and microphone, and transmits the data to the server in real time. Sensors, acting as monitoring tools, detect the baby's movements and sounds, and check their status. The server analyzes this data to determine the baby's sleep state and provides feedback as needed.

[0406] Furthermore, thermography and temperature sensors monitor the baby's body temperature and room temperature. The control system adjusts air conditioning and other settings appropriately based on the temperature data to create a comfortable environment for the baby.

[0407] The server notifies the user via the device when it determines that the baby has fallen asleep. It also has a function to immediately send an alert if an abnormality is detected. For example, if the baby's body temperature exceeds a set threshold, the server can issue an alert and notify the user's device.

[0408] This system configuration automates the entire process of getting a baby to sleep, reducing the burden on parents while ensuring the baby's safety.

[0409] The following describes the processing flow.

[0410] Step 1:

[0411] The user launches the app on their smartphone and enters basic information about their baby (age, music preferences, etc.). This information is then sent from the app to the server.

[0412] Step 2:

[0413] The server uses an AI algorithm to generate the optimal lullaby based on the information received from the user. This lullaby is selected considering past success data and current trends.

[0414] Step 3:

[0415] The generated lullaby is sent from the server to the terminal. The terminal plays this music through its speakers, creating an environment that helps soothe the baby to sleep.

[0416] Step 4:

[0417] The device monitors the baby's condition using a camera and microphone and transmits the data to a server in real time. The monitoring method involves detecting the baby's movements and sounds.

[0418] Step 5:

[0419] The server analyzes the video and audio data sent from the terminal to determine the baby's sleep state. If necessary, it regenerates an appropriate lullaby.

[0420] Step 6:

[0421] Furthermore, a temperature sensor built into the device monitors the baby's body temperature and the room temperature. Based on this data, the server adjusts the air conditioner settings to maintain a comfortable environment.

[0422] Step 7:

[0423] The server sends a notification to the user via the device when it determines that the baby has fallen asleep safely. It also immediately sends an alert to the user if any abnormalities (such as a high fever or prolonged crying) are detected.

[0424] (Example 1)

[0425] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0426] In today's busy lifestyle, efficiently getting babies to sleep is a crucial challenge for caregivers. Traditional methods make it difficult to accurately assess a baby's condition and maintain an appropriate environment, placing a heavy burden on caregivers. Furthermore, there is a need for a way to respond quickly to any health problems in babies, but existing systems are insufficient to address this.

[0427] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0428] In this invention, the server includes a generation means for generating optimal music to soothe a baby to sleep, a monitoring means equipped with a video recording device and an audio acquisition device for monitoring the baby's condition, and an environmental adjustment means for measuring and controlling the baby's body temperature and room temperature. This makes it possible to reduce the burden on caregivers and ensure safe and comfortable sleep for babies by providing appropriate music and environmental adjustments while monitoring the baby's condition in real time.

[0429] "Generation method" refers to the function or technology that generates optimal music for putting babies to sleep. This includes processes that automatically generate music using AI models and data analysis technologies.

[0430] "Monitoring means" refers to a mechanism equipped with a video recording device and an audio acquisition device used to monitor the baby's condition. This allows for real-time observation of the baby's behavior and sounds.

[0431] "Environmental adjustment means" refers to a mechanism for measuring the baby's body temperature and room temperature and controlling them as needed. Specifically, this includes functions that maintain an appropriate indoor environment by operating thermosensors, air conditioners, etc.

[0432] "Information processing means" refers to a function that analyzes data from the time the baby falls asleep and feeds the results back into music generation. This includes a process that uses data analysis technology to enhance the effectiveness of music generation.

[0433] "Notification means" refers to a function that notifies the user when the baby falls asleep. Specifically, this includes sending alerts and notifications to smartphones and other devices.

[0434] "Alarming mechanisms" refer to functions that issue warnings when an abnormality is detected. This includes issuing alerts to quickly inform the user of any abnormalities in the baby's health or environment.

[0435] This invention is a system for effectively getting babies to sleep, combining AI-powered music generation with real-time monitoring. This system primarily operates through the collaboration of a server, terminals, and users.

[0436] The server uses a generative AI model to generate music best suited for babies. Users input basic information about their baby and their musical preferences through a smartphone app, and this data is sent to the server. The server analyzes past data and trends and automatically generates music based on this analysis. For example, if a user requests "relaxing piano music," the generative AI model will be prompted with the command, "Generate a soothing piano lullaby for babies."

[0437] Meanwhile, the device plays a role in monitoring the baby's condition. Equipped with a camera and microphone, the device monitors the baby's behavior and sends the data to a server. The server analyzes this data to determine the baby's sleep state and any abnormalities.

[0438] Furthermore, the server measures temperature and humidity and controls air conditioning and other appliances to properly manage the environment around the baby. Once the user sets the environmental conditions, the device's sensors measure the indoor environment, and the server automatically adjusts the settings after analysis.

[0439] These features allow users to help their babies sleep safely and comfortably, reducing the burden of childcare.

[0440] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0441] Step 1:

[0442] The user launches the smartphone app and enters the baby's basic information (name, age, favorite music genre). The entered data is sent to the server. This allows the server to obtain basic data for music generation based on the information received from the user. Specifically, if the user selects "classical music," this selection is passed from the smartphone to the server.

[0443] Step 2:

[0444] The server uses a generative AI model to generate music best suited for a baby, based on data from the user. Input includes the user's music genre selection and the baby's age, while output is a music file generated by the AI ​​model. For example, the prompt "Generate relaxing classical music" is input to the model, and the generated music data is output. Specifically, the AI ​​composes the music in the cloud, and the generated file is saved on the server.

[0445] Step 3:

[0446] The server sends the generated music to the device. The device receives this music and plays it through a speaker in the room where the baby is. The input here is music data from the AI ​​model, and the output is the sound of the music being played. The music starts playing from the device's speaker, and the volume and playback time follow conditions set by the user beforehand.

[0447] Step 4:

[0448] The device sends data from its camera and microphone to a server to monitor the baby's condition. This monitoring data includes the baby's movements and sounds. This data is sent to the server as input and analyzed in real time. The server uses the data to determine the baby's condition. Specifically, video and audio of when the baby starts crying are sent to the server, and the server determines whether the baby is awake or not.

[0449] Step 5:

[0450] The server analyzes the monitoring data to confirm that the baby has fallen asleep and sends a notification to the user. The input is the monitoring data, and the output is a notification sent to the smartphone saying "The baby has fallen asleep." Once the server finishes its analysis and detects sleep, a notification is displayed on the user's smartphone.

[0451] Step 6:

[0452] The server adjusts the room temperature based on temperature sensor data. The server receives temperature data from the terminal and controls air conditioners and other devices as needed. Input is temperature sensor data, and output is an update of the temperature setting. If the server determines that the room temperature is outside the optimal range, the air conditioner's set temperature is automatically adjusted.

[0453] Step 7:

[0454] The server sends alerts to the user if any abnormalities occur in the baby or the surrounding environment. The server constantly monitors and checks environmental data to detect anomalies. Inputs are sensor data indicating abnormalities, and outputs are warning notifications such as "Body temperature is rising." If the baby's body temperature exceeds the set threshold, the server quickly sends a warning message to the user's smartphone.

[0455] (Application Example 1)

[0456] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0457] In modern childcare environments, a significant problem is the amount of time and effort parents spend getting their babies to sleep and maintaining their health. Furthermore, manual adjustments and monitoring are necessary to ensure the baby's safety and a comfortable sleep environment. To address these challenges, automated systems are needed.

[0458] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0459] In this invention, the server includes means for generating optimal music to lull the baby to sleep, monitoring means equipped with a camera and sound device for monitoring the baby's condition, and adjustment means for measuring and adjusting the baby's body temperature and room temperature. This makes it possible to automatically maintain a comfortable sleeping environment for the baby without parental intervention.

[0460] The "generation means" refers to a device that has the function of generating music that is optimal for putting a baby to sleep.

[0461] "Monitoring equipment" refers to devices that have the function of using a camera and an audio device to monitor the baby's condition.

[0462] A "regulating device" is a device that measures the baby's body temperature and room temperature and adjusts the environment based on those measurements.

[0463] The "analysis means" is a device that analyzes the baby's condition data and feeds the results back into music generation.

[0464] A "means of communication" refers to a system that notifies parents or caregivers when the baby falls asleep.

[0465] An "alert system" is a device that provides a warning when an anomaly is detected.

[0466] An "environmental control means" is a device that controls the air conditioning system based on environmental information to provide a comfortable environment for the baby.

[0467] "Audio output means" refers to a device that has the function of outputting generated music from an audio device.

[0468] A "reporting means" is a device that records the baby's condition, analyzes the patterns, and provides information to the user.

[0469] The system implementing this invention integrates multiple means to support the comfortable sleep and safety of babies. The server is responsible for processing data in real time at all times and taking necessary actions.

[0470] The server uses a generation mechanism to create the optimal lullaby based on the baby's preferred music type and past data, utilizing a generation AI model. This process employs machine learning algorithms using Python and TensorFlow. The generated music is played around the baby through speakers via an audio output mechanism.

[0471] As a monitoring method, a camera and audio device attached to the terminal monitor the baby's condition and transmit the data to a server. OpenCV is used to process the video data and analyze the baby's movements and sounds.

[0472] The adjustment mechanism automatically adjusts the room temperature via the air conditioning system based on data from temperature sensors. The server analyzes environmental and body temperature data collected using Firebase and makes appropriate settings.

[0473] Furthermore, the analysis system analyzes the baby's sleep data and provides feedback to the music generation system based on the results. This allows the accuracy of the generation system to improve over time.

[0474] As a means of communication, a notification will be sent to the user when it is determined that the baby has fallen asleep. This function will be implemented using a combination of Flask and a REST API.

[0475] The alert system immediately sends a warning to the user if the baby's body temperature exceeds a certain threshold or if any abnormality is detected.

[0476] As a concrete example, the generative AI model uses the following prompt: "Baby's basic information: 3 months old, preferred music type: classical. Please generate the best lullaby."

[0477] This system allows parents to entrust their baby's sleep environment to someone else with peace of mind, reducing the burden of childcare.

[0478] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0479] Step 1:

[0480] The user launches a smartphone app and enters basic information about their baby and their preferred music type. This information is sent to a server, where an AI model generates prompt messages. Based on the entered data, the server uses a generation tool to prepare to create the most suitable lullaby.

[0481] Step 2:

[0482] The server uses a generative AI model to generate lullabies based on prompt text. Using Python and TensorFlow, it analyzes historical data and trends to select the most suitable music. The generated lullaby is sent to a speaker via an audio output device. In this step, prompt text and historical data are used as input, and music data is obtained as output.

[0483] Step 3:

[0484] A device equipped with a camera and microphone monitors the baby's condition and collects audio and video data. The device uses OpenCV to analyze the video and audio and transmits the data to a server in real time. The input is video and audio data, and the output is the analyzed information about the baby's condition.

[0485] Step 4:

[0486] The server uses a control mechanism to receive data from the temperature sensor and issues instructions to control the air conditioner. It analyzes the body temperature and room temperature data collected via Firebase to maintain the room temperature at an optimal level for the baby. In this step, temperature data is used as input and air conditioner setting information is obtained as output.

[0487] Step 5:

[0488] The server determines the baby's sleep state. When the server determines that the baby has "fallen asleep," it sends a notification to the user via a communication method. If an abnormality is detected, it uses an alert method to immediately send a warning to the user. The input is the baby's status data, and the output is notification or warning information.

[0489] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0490] The present invention introduces a novel approach to the system that recognizes the user's emotions and utilizes them to help the baby fall asleep. The user operates the system using a smartphone application, providing information about getting the baby to sleep while simultaneously recording their own emotional state.

[0491] The device is equipped with an emotion engine that analyzes the user's emotions from their face and voice. It uses facial recognition and voice analysis technologies to recognize the user's emotions and sends that data to a server. This allows the user's stress level and relaxation level to be evaluated in real time.

[0492] The server integrates emotional data and baby status data to generate the most appropriate lullaby. This generation method adjusts the tempo and tone of the music, taking into account data from the emotional engine, and selects music that also helps the parent relax. In this way, a system is created in which the user's emotional state indirectly influences the baby's comfort.

[0493] As a monitoring tool, the camera and microphone installed in the device continuously monitor the baby's movements and cries, and transmit this information to a server. The analysis tool analyzes this data to determine if the baby's sleep has improved, and uses this information to improve future music generation.

[0494] Furthermore, the server uses notification and warning mechanisms to inform the user when it determines that the baby has fallen asleep or when an abnormality occurs. For example, if it determines that the user is experiencing stress, the notification mechanism can offer suggestions for relaxation.

[0495] For example, if the user is feeling sleepy, the emotion engine detects this and generates and plays relaxing classical music. Furthermore, if the user is feeling stressed, the tempo of the music can be adjusted to create a calmer atmosphere. In this way, the system of the present invention provides an integrated sleep environment that focuses on both the baby and the parent.

[0496] The following describes the processing flow.

[0497] Step 1:

[0498] The user launches the smartphone app and enters information about the baby (age, health, etc.). To enable emotion recognition, the user points their face at the camera and starts the app.

[0499] Step 2:

[0500] The device uses its camera and microphone to analyze the user's facial expressions and voice tone, and an emotion engine determines the user's emotional state. This data is then transmitted to the server in real time.

[0501] Step 3:

[0502] The server combines the received emotional data with previously accumulated data and uses an AI algorithm to generate the optimal lullaby. Music genre, tempo, volume, and other elements are adjusted according to the user's emotions.

[0503] Step 4:

[0504] The generated lullaby data is sent to the device. The device plays the music through its speaker, creating an environment that helps soothe the baby to sleep.

[0505] Step 5:

[0506] The device continues to monitor the baby using its camera and microphone, sending its movements and cries to the server. This allows for real-time monitoring of the situation.

[0507] Step 6:

[0508] The server analyzes both the baby's data and emotional data simultaneously, and evaluates the integrated daily data using analytical tools. It then provides feedback on particularly effective moments, which are used to improve future music generation.

[0509] Step 7:

[0510] Once the server confirms that the baby has fallen asleep, it sends a notification to the user via the device. It can also offer relaxation suggestions based on the user's emotions. If an anomaly is detected, it immediately sends an alert.

[0511] (Example 2)

[0512] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0513] There is a lack of effective lullabies and sleep training methods that take into account the impact of parents' emotional state on the baby's sleep environment. Traditional systems focus only on the baby's condition and do not fully utilize how parental stress levels and relaxation can help in getting the baby to sleep.

[0514] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0515] In this invention, the server includes an emotion analysis means, a music generation means, and a suggestion means. This makes it possible to analyze the user's emotional state in real time, generate music based on that analysis, and further make suggestions to the user to promote relaxation.

[0516] "Emotional analysis means" refers to a device that analyzes a user's facial expressions and voice to understand the user's emotional state.

[0517] "Music generation means" refers to a device or technology for generating music that is appropriate for the baby's condition or the user's emotions, based on acquired data.

[0518] The "integration means" is a device that integrates user emotion data and baby situation data and generates prompt sentences suitable for the generation AI model.

[0519] A "generative AI model" is an artificial intelligence model that generates new data or content based on specific prompt sentences.

[0520] "Observation methods" refer to devices such as cameras and microphones used to monitor the baby's movements and sounds and collect data.

[0521] A "notification mechanism" is a system that informs the user when the baby has fallen asleep.

[0522] "Suggestion methods" refer to devices and technologies used to offer suggestions to users that promote relaxation.

[0523] A "warning mechanism" is a mechanism that issues a warning to the user when the system detects an anomaly.

[0524] To implement this invention, the user needs to input information about getting the baby to sleep and record their own emotional state by operating a smartphone application. The user's facial expressions and voice are captured and analyzed in real time by an emotion analysis device via the smartphone.

[0525] The device uses facial recognition and voice analysis technologies to acquire user emotion data. This data is sent to a server and integrated with the baby's status data. The integration mechanism generates prompt statements for the AI ​​model to process based on this data.

[0526] The server uses a music generation system to create music optimized for the baby and parent based on prompt messages and emotional data. The tempo and tone of the music are adjusted according to the baby's condition and the parent's emotions. For example, a prompt message might say, "Generate music that promotes relaxation."

[0527] In this system, the terminal uses a camera and microphone as observation tools to continuously monitor the baby's movements and cries. This data is sent to a server where the baby's sleep patterns are analyzed in detail.

[0528] The server notifies the user via a notification system if an anomaly is detected or if it determines that the baby has fallen asleep. Furthermore, if the user's stress level is detected, the system can send suggestions to encourage relaxation. In this way, the system provides a sleep environment that prioritizes the comfort of both the baby and the parent.

[0529] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0530] Step 1:

[0531] The user launches a smartphone application and selects the lullaby mode. The input here consists of the user's selection and real-time data of facial expressions and voice. The device acquires this data using its camera and microphone and performs emotion analysis. Specifically, the device uses facial recognition and voice analysis technologies to determine the user's emotional state.

[0532] Step 2:

[0533] The terminal sends the results of its emotion analysis to the server. The input data sent is the user's emotional state data. The server receives this input and integrates it with other information about getting the baby to sleep. The data processing here involves combining and integrating the emotion data and the baby's situation data to generate prompt messages.

[0534] Step 3:

[0535] The server sends the generated prompt text to the generation AI model, instructing it to generate the most suitable music. The input at this stage consists of the prompt text and integrated emotional and situational data. The generation AI model receives this data and uses a music generation algorithm to output an appropriate lullaby. The generated music is adjusted in tempo and tone to suit the user and the baby's state.

[0536] Step 4:

[0537] The device plays the generated music. The input here is the music data output from the generation AI model. Specifically, the device plays the music through the speaker and adjusts the volume and playback timing.

[0538] Step 5:

[0539] The device continues to monitor the baby's movements and cries using its camera and microphone, and sends this data to the server. The monitoring input consists of the baby's movements and audio data. The server receives this data and evaluates the baby's sleep state. If the baby's condition improves, it generates feedback to be used for future music generation.

[0540] Step 6:

[0541] The server sends notifications and warnings to the user when the baby falls asleep or when it detects an abnormality. The input here is the baby's sleep evaluation data, and the output is the content of the notification to the user. Specifically, the server displays a notification on the user's smartphone and makes suggestions based on the situation.

[0542] (Application Example 2)

[0543] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0544] When getting a baby to sleep, parental fatigue and stress can be a major problem, increasing the burden of childcare. Furthermore, a parent's emotional state can directly affect a baby's calmness and sleep. Therefore, there is a need for effective childcare support systems that consider the well-being of both parents and babies.

[0545] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0546] In this invention, the server includes a generation means for generating music optimal for putting a baby to sleep, an emotion analysis and suggestion means for analyzing the user's emotions and providing advice and suggestions to encourage relaxation in the parent, and a commercial support means for providing childcare-related support based on the parent's emotional state within the store. This makes it possible to provide childcare support that takes the parent's emotional state into consideration, and to provide a comfortable environment for both the parent and the baby.

[0547] "Generating means" refers to a device or method that has the function of generating music that is optimal for putting a baby to sleep.

[0548] "Monitoring means" refers to devices or methods that use imaging devices and sound collection devices to monitor the condition of a baby.

[0549] "Environmental adjustment means" refers to devices or methods for measuring and appropriately controlling a baby's body temperature and room temperature.

[0550] "Analysis means" refers to devices or methods that analyze data from when a baby falls asleep and use that data to generate music.

[0551] "Means of communication" refers to devices or methods for providing appropriate notifications when a baby falls asleep.

[0552] A "warning mechanism" refers to a device or method used to issue a warning when an abnormality is detected.

[0553] "Emotional analysis and suggestion means" refers to a device or method for analyzing a user's emotions and providing advice or suggestions to parents to promote relaxation.

[0554] "Commercial support measures" refer to devices or methods for providing childcare-related support based on the emotional state of parents within a store.

[0555] The system of the present invention consists of a terminal, a server, and a user.

[0556] The device is equipped with an imaging device and an audio collection device, and its role is to collect and analyze the emotions of the baby and parent in real time. This analysis uses an emotion engine to analyze the user's emotional state using video data obtained from the camera and audio data collected from the microphone. For example, if the user is feeling stressed, the analysis results are sent to the server.

[0557] The server performs computational processing to optimize childcare support based on the received emotional data and child state data. To generate appropriate music using a generation method, a machine learning model is used to create music that takes into account past data and the parent's emotional state. This generated music not only helps babies relax and fall asleep, but also helps parents relax.

[0558] The server also provides advice and suggestions to help parents relax based on their condition. For example, if it detects that a parent is tired in the store, it can guide them to "please use the relaxation area in the store."

[0559] As an example of a prompt, using a prompt in the format of "Based on this user's emotional state, please provide the best parenting advice" allows the generative AI model to provide appropriate support information.

[0560] In this way, the system of the present invention is intended to provide an integrated childcare support environment that focuses on both parents and babies.

[0561] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0562] Step 1:

[0563] The device uses an imaging device and a voice acquisition device to collect data on the user and the baby in real time. It receives video data from the camera and audio data from the microphone as input. Using this data, an emotion engine analyzes facial expressions and voice tone to identify the user's emotional state. It generates emotional state data as output and provides it for the next step.

[0564] Step 2:

[0565] The terminal sends the emotional state data obtained in Step 1 to the server. It uses the emotional state data as input and transmits it to the server via the internet. After receiving the emotional data, the server stores it in its database and prepares to proceed to the next step. The output confirms that the data has been successfully saved to the server.

[0566] Step 3:

[0567] The server generates music for childcare support based on emotional state data and baby status data. It uses emotional state data and historical data such as the baby's sleep patterns as input. A generation AI model optimizes the music's tempo and melody to create lullabies that soothe both the user and the baby. The generated music data is then sent back to the device as output.

[0568] Step 4:

[0569] The device receives music data from the server and plays it through its speakers. It receives music data as input and uses an audio output interface to allow the user and the baby to listen. It adjusts the volume and playback timing to create a more relaxing environment for the user. It then plays the music into the environment as output.

[0570] Step 5:

[0571] The server continues to monitor emotional state data and the baby's condition, repeating the process in step 3 whenever new data becomes available. It receives real-time emotional and sleep data as input and updates the output with the most suitable lullabies and parenting advice at that moment. This ensures that appropriate support is always provided according to the user's and baby's condition.

[0572] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0573] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0574] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0575] [Fourth Embodiment]

[0576] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0577] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0578] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0579] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0580] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0581] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0582] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0583] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0584] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0585] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0586] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0587] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0588] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0589] The system of this invention integrates functions to assist in getting babies to sleep. Users can operate this system through a smartphone app. When the app is launched, the user enters the baby's basic information and preferred music type, and then begins the sleep-inducing process.

[0590] The server uses an AI algorithm to generate the most suitable lullaby for the baby based on user input data. This generation method analyzes past data and trends to select the most effective music. The generated lullaby is played through a speaker via the device.

[0591] The device monitors the baby's condition using a camera and microphone, and transmits the data to the server in real time. Sensors, acting as monitoring tools, detect the baby's movements and sounds, and check their status. The server analyzes this data to determine the baby's sleep state and provides feedback as needed.

[0592] Furthermore, thermography and temperature sensors monitor the baby's body temperature and room temperature. The control system adjusts air conditioning and other settings appropriately based on the temperature data to create a comfortable environment for the baby.

[0593] The server notifies the user via the device when it determines that the baby has fallen asleep. It also has a function to immediately send an alert if an abnormality is detected. For example, if the baby's body temperature exceeds a set threshold, the server can issue an alert and notify the user's device.

[0594] This system configuration automates the entire process of getting a baby to sleep, reducing the burden on parents while ensuring the baby's safety.

[0595] The following describes the processing flow.

[0596] Step 1:

[0597] The user launches the app on their smartphone and enters basic information about their baby (age, music preferences, etc.). This information is then sent from the app to the server.

[0598] Step 2:

[0599] The server uses an AI algorithm to generate the optimal lullaby based on the information received from the user. This lullaby is selected considering past success data and current trends.

[0600] Step 3:

[0601] The generated lullaby is sent from the server to the terminal. The terminal plays this music through its speakers, creating an environment that helps soothe the baby to sleep.

[0602] Step 4:

[0603] The device monitors the baby's condition using a camera and microphone and transmits the data to a server in real time. The monitoring method involves detecting the baby's movements and sounds.

[0604] Step 5:

[0605] The server analyzes the video and audio data sent from the terminal to determine the baby's sleep state. If necessary, it regenerates an appropriate lullaby.

[0606] Step 6:

[0607] Furthermore, a temperature sensor built into the device monitors the baby's body temperature and the room temperature. Based on this data, the server adjusts the air conditioner settings to maintain a comfortable environment.

[0608] Step 7:

[0609] The server sends a notification to the user via the device when it determines that the baby has fallen asleep safely. It also immediately sends an alert to the user if any abnormalities (such as a high fever or prolonged crying) are detected.

[0610] (Example 1)

[0611] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0612] In today's busy lifestyle, efficiently getting babies to sleep is a crucial challenge for caregivers. Traditional methods make it difficult to accurately assess a baby's condition and maintain an appropriate environment, placing a heavy burden on caregivers. Furthermore, there is a need for a way to respond quickly to any health problems in babies, but existing systems are insufficient to address this.

[0613] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0614] In this invention, the server includes a generation means for generating optimal music to soothe a baby to sleep, a monitoring means equipped with a video recording device and an audio acquisition device for monitoring the baby's condition, and an environmental adjustment means for measuring and controlling the baby's body temperature and room temperature. This makes it possible to reduce the burden on caregivers and ensure safe and comfortable sleep for babies by providing appropriate music and environmental adjustments while monitoring the baby's condition in real time.

[0615] "Generation method" refers to the function or technology that generates optimal music for putting babies to sleep. This includes processes that automatically generate music using AI models and data analysis technologies.

[0616] "Monitoring means" refers to a mechanism equipped with a video recording device and an audio acquisition device used to monitor the baby's condition. This allows for real-time observation of the baby's behavior and sounds.

[0617] "Environmental adjustment means" refers to a mechanism for measuring the baby's body temperature and room temperature and controlling them as needed. Specifically, this includes functions that maintain an appropriate indoor environment by operating thermosensors, air conditioners, etc.

[0618] "Information processing means" refers to a function that analyzes data from the time the baby falls asleep and feeds the results back into music generation. This includes a process that uses data analysis technology to enhance the effectiveness of music generation.

[0619] "Notification means" refers to a function that notifies the user when the baby falls asleep. Specifically, this includes sending alerts and notifications to smartphones and other devices.

[0620] "Alarming mechanisms" refer to functions that issue warnings when an abnormality is detected. This includes issuing alerts to quickly inform the user of any abnormalities in the baby's health or environment.

[0621] This invention is a system for effectively getting babies to sleep, combining AI-powered music generation with real-time monitoring. This system primarily operates through the collaboration of a server, terminals, and users.

[0622] The server uses a generative AI model to generate music best suited for babies. Users input basic information about their baby and their musical preferences through a smartphone app, and this data is sent to the server. The server analyzes past data and trends and automatically generates music based on this analysis. For example, if a user requests "relaxing piano music," the generative AI model will be prompted with the command, "Generate a soothing piano lullaby for babies."

[0623] Meanwhile, the device plays a role in monitoring the baby's condition. Equipped with a camera and microphone, the device monitors the baby's behavior and sends the data to a server. The server analyzes this data to determine the baby's sleep state and any abnormalities.

[0624] Furthermore, the server measures temperature and humidity and controls air conditioning and other appliances to properly manage the environment around the baby. Once the user sets the environmental conditions, the device's sensors measure the indoor environment, and the server automatically adjusts the settings after analysis.

[0625] These features allow users to help their babies sleep safely and comfortably, reducing the burden of childcare.

[0626] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0627] Step 1:

[0628] The user launches the smartphone app and enters the baby's basic information (name, age, favorite music genre). The entered data is sent to the server. This allows the server to obtain basic data for music generation based on the information received from the user. Specifically, if the user selects "classical music," this selection is passed from the smartphone to the server.

[0629] Step 2:

[0630] The server uses a generative AI model to generate music best suited for a baby, based on data from the user. Input includes the user's music genre selection and the baby's age, while output is a music file generated by the AI ​​model. For example, the prompt "Generate relaxing classical music" is input to the model, and the generated music data is output. Specifically, the AI ​​composes the music in the cloud, and the generated file is saved on the server.

[0631] Step 3:

[0632] The server sends the generated music to the device. The device receives this music and plays it through a speaker in the room where the baby is. The input here is music data from the AI ​​model, and the output is the sound of the music being played. The music starts playing from the device's speaker, and the volume and playback time follow conditions set by the user beforehand.

[0633] Step 4:

[0634] The device sends data from its camera and microphone to a server to monitor the baby's condition. This monitoring data includes the baby's movements and sounds. This data is sent to the server as input and analyzed in real time. The server uses the data to determine the baby's condition. Specifically, video and audio of when the baby starts crying are sent to the server, and the server determines whether the baby is awake or not.

[0635] Step 5:

[0636] The server analyzes the monitoring data to confirm that the baby has fallen asleep and sends a notification to the user. The input is the monitoring data, and the output is a notification sent to the smartphone saying "The baby has fallen asleep." Once the server finishes its analysis and detects sleep, a notification is displayed on the user's smartphone.

[0637] Step 6:

[0638] The server adjusts the room temperature based on temperature sensor data. The server receives temperature data from the terminal and controls air conditioners and other devices as needed. Input is temperature sensor data, and output is an update of the temperature setting. If the server determines that the room temperature is outside the optimal range, the air conditioner's set temperature is automatically adjusted.

[0639] Step 7:

[0640] The server sends alerts to the user if any abnormalities occur in the baby or the surrounding environment. The server constantly monitors and checks environmental data to detect anomalies. Inputs are sensor data indicating abnormalities, and outputs are warning notifications such as "Body temperature is rising." If the baby's body temperature exceeds the set threshold, the server quickly sends a warning message to the user's smartphone.

[0641] (Application Example 1)

[0642] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0643] In modern childcare environments, a significant problem is the amount of time and effort parents spend getting their babies to sleep and maintaining their health. Furthermore, manual adjustments and monitoring are necessary to ensure the baby's safety and a comfortable sleep environment. To address these challenges, automated systems are needed.

[0644] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0645] In this invention, the server includes means for generating optimal music to lull the baby to sleep, monitoring means equipped with a camera and sound device for monitoring the baby's condition, and adjustment means for measuring and adjusting the baby's body temperature and room temperature. This makes it possible to automatically maintain a comfortable sleeping environment for the baby without parental intervention.

[0646] The "generation means" refers to a device that has the function of generating music that is optimal for putting a baby to sleep.

[0647] "Monitoring equipment" refers to devices that have the function of using a camera and an audio device to monitor the baby's condition.

[0648] A "regulating device" is a device that measures the baby's body temperature and room temperature and adjusts the environment based on those measurements.

[0649] The "analysis means" is a device that analyzes the baby's condition data and feeds the results back into music generation.

[0650] A "means of communication" refers to a system that notifies parents or caregivers when the baby falls asleep.

[0651] An "alert system" is a device that provides a warning when an anomaly is detected.

[0652] An "environmental control means" is a device that controls the air conditioning system based on environmental information to provide a comfortable environment for the baby.

[0653] "Audio output means" refers to a device that has the function of outputting generated music from an audio device.

[0654] A "reporting means" is a device that records the baby's condition, analyzes the patterns, and provides information to the user.

[0655] The system implementing this invention integrates multiple means to support the comfortable sleep and safety of babies. The server is responsible for processing data in real time at all times and taking necessary actions.

[0656] The server uses a generation mechanism to create the optimal lullaby based on the baby's preferred music type and past data, utilizing a generation AI model. This process employs machine learning algorithms using Python and TensorFlow. The generated music is played around the baby through speakers via an audio output mechanism.

[0657] As a monitoring method, a camera and audio device attached to the terminal monitor the baby's condition and transmit the data to a server. OpenCV is used to process the video data and analyze the baby's movements and sounds.

[0658] The adjustment mechanism automatically adjusts the room temperature via the air conditioning system based on data from temperature sensors. The server analyzes environmental and body temperature data collected using Firebase and makes appropriate settings.

[0659] Furthermore, the analysis system analyzes the baby's sleep data and provides feedback to the music generation system based on the results. This allows the accuracy of the generation system to improve over time.

[0660] As a means of communication, a notification will be sent to the user when it is determined that the baby has fallen asleep. This function will be implemented using a combination of Flask and a REST API.

[0661] The alert system immediately sends a warning to the user if the baby's body temperature exceeds a certain threshold or if any abnormality is detected.

[0662] As a concrete example, the generative AI model uses the following prompt: "Baby's basic information: 3 months old, preferred music type: classical. Please generate the best lullaby."

[0663] This system allows parents to entrust their baby's sleep environment to someone else with peace of mind, reducing the burden of childcare.

[0664] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0665] Step 1:

[0666] The user launches a smartphone app and enters basic information about their baby and their preferred music type. This information is sent to a server, where an AI model generates prompt messages. Based on the entered data, the server uses a generation tool to prepare to create the most suitable lullaby.

[0667] Step 2:

[0668] The server uses a generative AI model to generate lullabies based on prompt text. Using Python and TensorFlow, it analyzes historical data and trends to select the most suitable music. The generated lullaby is sent to a speaker via an audio output device. In this step, prompt text and historical data are used as input, and music data is obtained as output.

[0669] Step 3:

[0670] A device equipped with a camera and microphone monitors the baby's condition and collects audio and video data. The device uses OpenCV to analyze the video and audio and transmits the data to a server in real time. The input is video and audio data, and the output is the analyzed information about the baby's condition.

[0671] Step 4:

[0672] The server uses a control mechanism to receive data from the temperature sensor and issues instructions to control the air conditioner. It analyzes the body temperature and room temperature data collected via Firebase to maintain the room temperature at an optimal level for the baby. In this step, temperature data is used as input and air conditioner setting information is obtained as output.

[0673] Step 5:

[0674] The server determines the baby's sleep state. When the server determines that the baby has "fallen asleep," it sends a notification to the user via a communication method. If an abnormality is detected, it uses an alert method to immediately send a warning to the user. The input is the baby's status data, and the output is notification or warning information.

[0675] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0676] The present invention introduces a novel approach to the system that recognizes the user's emotions and utilizes them to help the baby fall asleep. The user operates the system using a smartphone application, providing information about getting the baby to sleep while simultaneously recording their own emotional state.

[0677] The device is equipped with an emotion engine that analyzes the user's emotions from their face and voice. It uses facial recognition and voice analysis technologies to recognize the user's emotions and sends that data to a server. This allows the user's stress level and relaxation level to be evaluated in real time.

[0678] The server integrates emotional data and baby status data to generate the most appropriate lullaby. This generation method adjusts the tempo and tone of the music, taking into account data from the emotional engine, and selects music that also helps the parent relax. In this way, a system is created in which the user's emotional state indirectly influences the baby's comfort.

[0679] As a monitoring tool, the camera and microphone installed in the device continuously monitor the baby's movements and cries, and transmit this information to a server. The analysis tool analyzes this data to determine if the baby's sleep has improved, and uses this information to improve future music generation.

[0680] Furthermore, the server uses notification and warning mechanisms to inform the user when it determines that the baby has fallen asleep or when an abnormality occurs. For example, if it determines that the user is experiencing stress, the notification mechanism can offer suggestions for relaxation.

[0681] For example, if the user is feeling sleepy, the emotion engine detects this and generates and plays relaxing classical music. Furthermore, if the user is feeling stressed, the tempo of the music can be adjusted to create a calmer atmosphere. In this way, the system of the present invention provides an integrated sleep environment that focuses on both the baby and the parent.

[0682] The following describes the processing flow.

[0683] Step 1:

[0684] The user launches the smartphone app and enters information about the baby (age, health, etc.). To enable emotion recognition, the user points their face at the camera and starts the app.

[0685] Step 2:

[0686] The device uses its camera and microphone to analyze the user's facial expressions and voice tone, and an emotion engine determines the user's emotional state. This data is then transmitted to the server in real time.

[0687] Step 3:

[0688] The server combines the received emotional data with previously accumulated data and uses an AI algorithm to generate the optimal lullaby. Music genre, tempo, volume, and other elements are adjusted according to the user's emotions.

[0689] Step 4:

[0690] The generated lullaby data is sent to the device. The device plays the music through its speaker, creating an environment that helps soothe the baby to sleep.

[0691] Step 5:

[0692] The device continues to monitor the baby using its camera and microphone, sending its movements and cries to the server. This allows for real-time monitoring of the situation.

[0693] Step 6:

[0694] The server analyzes both the baby's data and emotional data simultaneously, and evaluates the integrated daily data using analytical tools. It then provides feedback on particularly effective moments, which are used to improve future music generation.

[0695] Step 7:

[0696] Once the server confirms that the baby has fallen asleep, it sends a notification to the user via the device. It can also offer relaxation suggestions based on the user's emotions. If an anomaly is detected, it immediately sends an alert.

[0697] (Example 2)

[0698] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0699] There is a lack of effective lullabies and sleep training methods that take into account the impact of parents' emotional state on the baby's sleep environment. Traditional systems focus only on the baby's condition and do not fully utilize how parental stress levels and relaxation can help in getting the baby to sleep.

[0700] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0701] In this invention, the server includes an emotion analysis means, a music generation means, and a suggestion means. This makes it possible to analyze the user's emotional state in real time, generate music based on that analysis, and further make suggestions to the user to promote relaxation.

[0702] "Emotional analysis means" refers to a device that analyzes a user's facial expressions and voice to understand the user's emotional state.

[0703] "Music generation means" refers to a device or technology for generating music that is appropriate for the baby's condition or the user's emotions, based on acquired data.

[0704] The "integration means" is a device that integrates user emotion data and baby situation data and generates prompt sentences suitable for the generation AI model.

[0705] A "generative AI model" is an artificial intelligence model that generates new data or content based on specific prompt sentences.

[0706] "Observation methods" refer to devices such as cameras and microphones used to monitor the baby's movements and sounds and collect data.

[0707] A "notification mechanism" is a system that informs the user when the baby has fallen asleep.

[0708] "Suggestion methods" refer to devices and technologies used to offer suggestions to users that promote relaxation.

[0709] A "warning mechanism" is a mechanism that issues a warning to the user when the system detects an anomaly.

[0710] To implement this invention, the user needs to input information about getting the baby to sleep and record their own emotional state by operating a smartphone application. The user's facial expressions and voice are captured and analyzed in real time by an emotion analysis device via the smartphone.

[0711] The device uses facial recognition and voice analysis technologies to acquire user emotion data. This data is sent to a server and integrated with the baby's status data. The integration mechanism generates prompt sentences based on this data for processing by a generative AI model.

[0712] The server uses a music generation system to create music optimized for the baby and parent based on prompt messages and emotional data. The tempo and tone of the music are adjusted according to the baby's condition and the parent's emotions. For example, a prompt message might say, "Generate music that promotes relaxation."

[0713] In this system, the terminal uses a camera and microphone as observation tools to continuously monitor the baby's movements and cries. This data is sent to a server where the baby's sleep patterns are analyzed in detail.

[0714] The server notifies the user via a notification system if an anomaly is detected or if it determines that the baby has fallen asleep. Furthermore, if the user's stress level is detected, the system can send suggestions to encourage relaxation. In this way, the system provides a sleep environment that prioritizes the comfort of both the baby and the parent.

[0715] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0716] Step 1:

[0717] The user launches a smartphone application and selects the lullaby mode. The input here consists of the user's selection and real-time data of facial expressions and voice. The device acquires this data using its camera and microphone and performs emotion analysis. Specifically, the device uses facial recognition and voice analysis technologies to determine the user's emotional state.

[0718] Step 2:

[0719] The terminal sends the results of its emotion analysis to the server. The input data sent is the user's emotional state data. The server receives this input and integrates it with other information about getting the baby to sleep. The data processing here involves combining and integrating the emotion data and the baby's situation data to generate prompt messages.

[0720] Step 3:

[0721] The server sends the generated prompt text to the generation AI model, instructing it to generate the most suitable music. The input at this stage consists of the prompt text and integrated emotional and situational data. The generation AI model receives this data and uses a music generation algorithm to output an appropriate lullaby. The generated music is adjusted in tempo and tone to suit the user and the baby's state.

[0722] Step 4:

[0723] The device plays the generated music. The input here is the music data output from the generation AI model. Specifically, the device plays the music through the speaker and adjusts the volume and playback timing.

[0724] Step 5:

[0725] The device continues to monitor the baby's movements and cries using its camera and microphone, and sends this data to the server. The monitoring input consists of the baby's movements and audio data. The server receives this data and evaluates the baby's sleep state. If the baby's condition improves, it generates feedback to be used for future music generation.

[0726] Step 6:

[0727] The server sends notifications and warnings to the user when the baby falls asleep or when it detects an abnormality. The input here is the baby's sleep evaluation data, and the output is the content of the notification to the user. Specifically, the server displays a notification on the user's smartphone and makes suggestions based on the situation.

[0728] (Application Example 2)

[0729] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0730] When getting a baby to sleep, parental fatigue and stress can be a major problem, increasing the burden of childcare. Furthermore, a parent's emotional state can directly affect a baby's calmness and sleep. Therefore, there is a need for effective childcare support systems that consider the well-being of both parents and babies.

[0731] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0732] In this invention, the server includes a generation means for generating music optimal for putting a baby to sleep, an emotion analysis and suggestion means for analyzing the user's emotions and providing advice and suggestions to encourage relaxation in the parent, and a commercial support means for providing childcare-related support based on the parent's emotional state within the store. This makes it possible to provide childcare support that takes the parent's emotional state into consideration, and to provide a comfortable environment for both the parent and the baby.

[0733] "Generating means" refers to a device or method that has the function of generating music that is optimal for putting a baby to sleep.

[0734] "Monitoring means" refers to devices or methods that use imaging devices and sound collection devices to monitor the condition of a baby.

[0735] "Environmental adjustment means" refers to devices or methods for measuring and appropriately controlling a baby's body temperature and room temperature.

[0736] "Analysis means" refers to devices or methods that analyze data from when a baby falls asleep and use that data to generate music.

[0737] "Means of communication" refers to devices or methods for providing appropriate notifications when a baby falls asleep.

[0738] A "warning mechanism" refers to a device or method used to issue a warning when an abnormality is detected.

[0739] "Emotional analysis and suggestion means" refers to a device or method for analyzing a user's emotions and providing advice or suggestions to parents to promote relaxation.

[0740] "Commercial support measures" refer to devices or methods for providing childcare-related support based on the emotional state of parents within a store.

[0741] The system of the present invention consists of a terminal, a server, and a user.

[0742] The device is equipped with an imaging device and an audio collection device, and its role is to collect and analyze the emotions of the baby and parent in real time. This analysis uses an emotion engine to analyze the user's emotional state using video data obtained from the camera and audio data collected from the microphone. For example, if the user is feeling stressed, the analysis results are sent to the server.

[0743] The server performs computational processing to optimize childcare support based on the received emotional data and child state data. To generate appropriate music using a generation method, a machine learning model is used to create music that takes into account past data and the parent's emotional state. This generated music not only helps babies relax and fall asleep, but also helps parents relax.

[0744] The server also provides advice and suggestions to help parents relax based on their condition. For example, if it detects that a parent is tired in the store, it can guide them to "please use the relaxation area in the store."

[0745] As an example of a prompt, using a prompt in the format of "Based on this user's emotional state, please provide the best parenting advice" allows the generative AI model to provide appropriate support information.

[0746] In this way, the system of the present invention is intended to provide an integrated childcare support environment that focuses on both parents and babies.

[0747] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0748] Step 1:

[0749] The device uses an imaging device and a voice acquisition device to collect data on the user and the baby in real time. It receives video data from the camera and audio data from the microphone as input. Using this data, an emotion engine analyzes facial expressions and voice tone to identify the user's emotional state. It generates emotional state data as output and provides it for the next step.

[0750] Step 2:

[0751] The terminal sends the emotional state data obtained in Step 1 to the server. It uses the emotional state data as input and transmits it to the server via the internet. After receiving the emotional data, the server stores it in its database and prepares to proceed to the next step. The output confirms that the data has been successfully saved to the server.

[0752] Step 3:

[0753] The server generates music for childcare support based on emotional state data and baby status data. It uses emotional state data and historical data such as the baby's sleep patterns as input. A generation AI model optimizes the music's tempo and melody to create lullabies that soothe both the user and the baby. The generated music data is then sent back to the device as output.

[0754] Step 4:

[0755] The device receives music data from the server and plays it through its speakers. It receives music data as input and uses an audio output interface to allow the user and the baby to listen. It adjusts the volume and playback timing to create a more relaxing environment for the user. It then plays the music into the environment as output.

[0756] Step 5:

[0757] The server continues to monitor emotional state data and the baby's condition, repeating the process in step 3 whenever new data becomes available. It receives real-time emotional and sleep data as input and updates the output with the most suitable lullabies and parenting advice at that moment. This ensures that appropriate support is always provided according to the user's and baby's condition.

[0758] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0759] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0760] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0761] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0762] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0763] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0764] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0765] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0766] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0767] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0768] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0769] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0770] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0771] 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.

[0772] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0773] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0774] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0775] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0776] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0777] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0778] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0779] The following is further disclosed regarding the embodiments described above.

[0780] (Claim 1)

[0781] A means for generating music that is optimal for getting a baby to sleep,

[0782] A monitoring system equipped with a camera and microphone for monitoring the baby's condition,

[0783] Control means for measuring and controlling the baby's body temperature and room temperature,

[0784] An analytical method for analyzing data on how babies fall asleep and feeding that data back into music generation,

[0785] A notification method that alerts you when the baby falls asleep,

[0786] A system that includes a warning mechanism to issue a warning when an anomaly is detected.

[0787] (Claim 2)

[0788] The system according to claim 1, wherein the generation means generates music using a machine learning model with respect to past data.

[0789] (Claim 3)

[0790] The system according to claim 1, wherein the control means automatically adjusts the room temperature based on the baby's body temperature.

[0791] "Example 1"

[0792] (Claim 1)

[0793] A means for generating music that is optimal for getting a baby to sleep,

[0794] A monitoring means equipped with a video recording device and an audio acquisition device for monitoring the condition of a baby,

[0795] An environmental adjustment means for measuring and controlling the baby's body temperature and room temperature,

[0796] An information processing method for analyzing data on how a baby falls asleep and feeding that data back into music generation,

[0797] A notification system that alerts you when the baby falls asleep,

[0798] A system that includes an alarm mechanism to issue a warning when an anomaly is detected.

[0799] (Claim 2)

[0800] The system according to claim 1, wherein the generation means generates music using an artificial intelligence model based on past information.

[0801] (Claim 3)

[0802] The system according to claim 1, wherein the environmental adjustment means automatically adjusts the room temperature based on the baby's body temperature.

[0803] "Application Example 1"

[0804] (Claim 1)

[0805] A means of generating the optimal music for getting a baby to sleep,

[0806] A monitoring system equipped with a camera and an acoustic device for monitoring the condition of a baby,

[0807] A means for measuring and adjusting the baby's body temperature and room temperature,

[0808] An analytical method for analyzing baby condition data and feeding it back into music generation,

[0809] A means of communication to notify when the baby falls asleep,

[0810] An alert system that issues a warning when an anomaly is detected,

[0811] An environmental control means for controlling an air conditioner based on environmental information to provide a comfortable environment for a baby,

[0812] Audio output means for outputting generated music from audio equipment,

[0813] A system that includes a means for recording the baby's condition, analyzing the patterns of that condition, and providing information to the user through reports.

[0814] (Claim 2)

[0815] The system according to claim 1, wherein the generation means comprises means for generating music using an AI model with past digital data.

[0816] (Claim 3)

[0817] The system according to claim 1, wherein the adjustment means is a means for automatically controlling the air conditioning system based on the baby's body temperature and room temperature.

[0818] "Example 2 of combining an emotion engine"

[0819] (Claim 1)

[0820] A means of analyzing user emotional data,

[0821] A music generation means that generates optimal music based on the above emotional data,

[0822] An integration means for integrating the user's emotional state and the baby's situation to generate prompt text,

[0823] A generation means that sends the above prompt message to a generation AI model and generates music,

[0824] Observation means for monitoring the baby's movements and sounds,

[0825] A notification method that alerts you when the baby falls asleep,

[0826] A suggestion method that offers suggestions to encourage relaxation in the user,

[0827] A system that includes a warning mechanism to issue a warning when an anomaly is detected.

[0828] (Claim 2)

[0829] The system according to claim 1, wherein the emotion analysis means analyzes the user's emotions using facial recognition technology and voice analysis technology.

[0830] (Claim 3)

[0831] The system according to claim 1, wherein the integration means integrates user emotion data and baby status data to generate prompt sentences in real time.

[0832] "Application example 2 when combining with an emotional engine"

[0833] (Claim 1)

[0834] A means for generating music that is optimal for getting a baby to sleep,

[0835] A monitoring means equipped with an imaging device and a sound collection device for monitoring the condition of a baby,

[0836] An environmental adjustment means for measuring and controlling the baby's body temperature and room temperature,

[0837] An analytical method for analyzing data on how babies fall asleep and feeding that data back into music generation,

[0838] A means of communication to notify when the baby falls asleep,

[0839] A warning mechanism that issues an alert when an anomaly is detected,

[0840] An emotion analysis and suggestion method that analyzes the user's emotions and provides advice and suggestions to parents to promote relaxation,

[0841] A system that includes commercial support measures that provide childcare-related support based on the emotional state of parents within a store.

[0842] (Claim 2)

[0843] The generation method generates music using a machine learning model based on past data.

[0844] The system according to claim 1, which generates childcare support suggestions that take into account the user's emotional state.

[0845] (Claim 3)

[0846] The system according to claim 1, wherein the environmental adjustment means automatically adjusts the room temperature based on the emotional state of the baby and the parent. [Explanation of Symbols]

[0847] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for generating music that is optimal for getting a baby to sleep, A monitoring system equipped with a camera and microphone for monitoring the baby's condition, Control means for measuring and controlling the baby's body temperature and room temperature, An analytical method for analyzing data on how babies fall asleep and feeding that data back into music generation, A notification method that alerts you when the baby falls asleep, A system that includes a warning mechanism to issue a warning when an anomaly is detected.

2. The system according to claim 1, wherein the generation means generates music using a machine learning model with respect to past data.

3. The system according to claim 1, wherein the control means automatically adjusts the room temperature based on the baby's body temperature.

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