System

Abstract

A system is provided.SOLUTION: A system for providing a service by replacing a device in accordance with growth of a user and handing over data, the system comprising: means for inputting basic information of a neonate; means for collecting data by monitoring motion and sound of the neonate; means for analyzing the collected data and providing advice to the user; means for making an emergency contact when an abnormality is detected; and means for handing over data to a next device in accordance with growth of the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional childcare support devices only provide services for a specific age group, and it is not easy to replace devices or transfer data as children grow. This makes it difficult to provide consistent support that responds to the user's growth and changes in environment, and increases the burden on parents and guardians. [Means for solving the problem]

[0005] The present invention is a system that provides services by replacing devices as the user grows and transferring data.By providing a system that includes a means for inputting basic information about the newborn, a means for monitoring the newborn's movements and voice and collecting data, a means for analyzing the collected data and providing advice to the user, a means for making emergency contact when an abnormality is detected, and a means for transferring data to the next device as the user grows, it is possible to provide consistent childcare support as the child grows and reduce the burden on parents and guardians.

[0006] "Users" are people who use the system, primarily referring to newborns and growing children, as well as their parents and guardians.

[0007] "Growth" refers to the user's progression in age and abilities from newborn to toddler and beyond.

[0008] The term "device" refers to an electronic device used in the present invention, and refers to hardware having a specific function.

[0009] "Replacement" means the retirement of an existing device and its replacement with a new device.

[0010] "Data transfer" is the process of transferring information stored on an old device to a new device.

[0011] "Services" means the assistance and functions provided by the System to Users, in particular support related to childcare.

[0012] "Newborn" refers to a baby who has just been born, generally a child under one year old.

[0013] "Means for entering basic information" refers to the interface for entering initial information such as the user's name, date of birth, and gender into the system.

[0014] "Means for monitoring and collecting data" refers to the ability to monitor the movements and sounds of the newborn via the device and collect that data.

[0015] "Means of analysis and providing advice" refers to the function of analyzing collected data and providing specific parenting advice to users.

[0016] "Means for detecting abnormalities" refers to equipment or software that has the ability to monitor and detect abnormalities that are distinct from a newborn's normal behavior or reactions.

[0017] "Means for making emergency contact" refers to a function that automatically contacts pre-set contacts when an abnormality is detected. [Brief explanation of the drawings]

[0018] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0019] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0020] First, the terms used in the following description will be explained.

[0021] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0022] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0023] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0024] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0026] [First embodiment]

[0027] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0028] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0029] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0030] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0031] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0032] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0033] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0034] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0036] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0037] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0038] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0039] The following system and its processing will be described as an embodiment of the present invention. This system provides optimized services by replacing devices according to the needs of users growing from newborns, while inheriting personal data.

[0040] Overall system configuration

[0041] The system consists of the following main components:

[0042] 1. A way to enter basic information about newborns

[0043] 2. A means of collecting data by monitoring the movements and sounds of newborns

[0044] 3. A means of analyzing collected data and providing advice to users

[0045] 4. Means of emergency contact when an abnormality is detected

[0046] 5. A way to transfer data to the next device as users grow

[0047] Each element is specifically implemented as follows:

[0048] A means of entering basic information about a newborn

[0049] For the initial setup, the user uses a smartphone app to enter basic information such as the newborn's name, date of birth, and gender. The device receives this information, sends it to a server, and stores it in a database. This information forms the basis for personalization in all subsequent processes.

[0050] A means of monitoring and collecting data on newborn movements and sounds

[0051] The device uses a camera and microphone to monitor the newborn's movements and sounds 24 / 7, including the baby's crying, sleep patterns, and body movements, and the collected data is sent to a server in real time.

[0052] A means of analyzing collected data and providing advice to users

[0053] The server analyzes the collected data and models the newborn's daily rhythm and characteristics. Based on the analysis results, it generates specific childcare advice for the user. For example, if a baby frequently cries at night, the server will provide the user with advice such as "play music at a steady rhythm." The device then notifies the user of this advice via a smartphone app.

[0054] A means of making emergency contact when an abnormality is detected

[0055] The device detects abnormal movements or sounds from the newborn. The server analyzes the abnormal data, determines whether it is an emergency, and automatically sends an emergency notification to designated contacts (e.g., emergency services, parents). The user receives the emergency notification via a smartphone app, allowing them to respond quickly.

[0056] A way to transfer data to the next device as users grow

[0057] When the user turns two years old, the server sends a notification to transition to a device suitable for the next stage of development. The user purchases a new device and sets it up. The device establishes the new device's Wi-Fi settings and connects to the server. The server transfers all personal data to the new device and continues to provide consistent support.

[0058] Processing explanation in natural language with concrete examples

[0059] For example, when a user enters basic information about a newborn into a smartphone app, the device sends this information to a server and stores it in a database. The device then uses a camera and microphone to monitor the baby's movements and sounds 24 / 7. The collected data is sent to the server in real time, which analyzes it. For example, if the server detects that the baby is crying frequently at night, it will notify the user through the smartphone app with advice to "play music at a regular rhythm." Furthermore, if the device detects abnormal movements or sounds from the baby, the server will determine this is an emergency and automatically contact emergency services. Finally, when the user turns two years old, the server will transfer the data to a new device, providing consistent support for childcare.

[0060] This allows users to receive consistent support as their child grows from birth, reducing the burden of childcare.

[0061] The processing flow will be explained below.

[0062] Step 1:

[0063] The user opens the smartphone app and connects the new monitoring camera device to Wi-Fi.

[0064] Step 2:

[0065] The device checks the Internet connection and performs a connection test to the server.

[0066] Step 3:

[0067] The server verifies the connection and sends the settings screen to the user.

[0068] Step 4:

[0069] The user enters basic information about the newborn baby, such as their name, date of birth, and gender, on the app's settings screen.

[0070] Step 5:

[0071] The terminal receives the information entered by the user and transmits it to the server.

[0072] Step 6:

[0073] The server stores the received information in a database.

[0074] Step 7:

[0075] The device uses a camera and microphone to monitor the newborn's movements and sounds 24 hours a day.

[0076] Step 8:

[0077] The data collected by the device is sent to the server in real time.

[0078] Step 9:

[0079] The server receives the data and performs pre-processing (noise removal, time synchronization, etc.).

[0080] Step 10:

[0081] The server analyzes the preprocessed data and models the newborn's daily rhythms and characteristics.

[0082] Step 11:

[0083] The server generates specific child-rearing advice based on the analysis results.

[0084] Step 12:

[0085] The server notifies the user of the generated advice.

[0086] Step 13:

[0087] The device displays a notification to the user via a smartphone app, saying, "The baby has started crying. Please play music."

[0088] Step 14:

[0089] The user confirms the notification and starts playing music in the app.

[0090] Step 15:

[0091] The device will play music and continue to monitor your baby's condition.

[0092] Step 16:

[0093] The device detects abnormal movements or sounds from the baby.

[0094] Step 17:

[0095] Any abnormality information detected by the device is immediately sent to the server.

[0096] Step 18:

[0097] The server analyzes the abnormal data and determines whether it is an emergency.

[0098] Step 19:

[0099] If the server determines that an emergency exists, it will automatically send an emergency notification to the designated contacts.

[0100] Step 20:

[0101] The device sends an emergency notification to the user, displaying the message "Your baby is in danger. Call an ambulance."

[0102] Step 21:

[0103] Users can check emergency notifications and take appropriate action immediately.

[0104] Step 22:

[0105] The server sends a notification to the user to transition to a new device when the user turns two years old.

[0106] Step 23:

[0107] The device will display a message saying "Please move to the next stage device" and provide guidelines.

[0108] Step 24:

[0109] A user purchases a new device and sets it up for initial setup.

[0110] Step 25:

[0111] The device establishes a Wi-Fi connection for the new device and connects to the server.

[0112] Step 26:

[0113] The server will transfer all existing data to the new device.

[0114] Step 27:

[0115] The device receives the migrated data and starts new support tailored to the growing user base.

[0116] Step 28:

[0117] The server analyzes the monitoring data from the new device and continues to provide consistent parenting support.

[0118] Example 1

[0119] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0120] Conventional childcare support systems have the problem of making it difficult to properly replace devices and transfer data as the baby grows from birth. Furthermore, data collection, analysis, and advice provision of newborn movements and voices are often inconsistent, making it difficult to respond quickly in emergencies. This creates the problem of parents being unable to receive consistent childcare support and increasing the burden of childcare on parents.

[0121] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0122] In this invention, the server includes means for inputting basic information, means for monitoring movements and sounds and collecting data, means for analyzing the collected data and providing advice, means for making emergency contact when an abnormality is detected, means for transferring data to the next device as the user grows, means for analyzing the collected data using a machine learning model and modeling daily rhythms and characteristics, and means for automatically making emergency contact and notifying designated contacts. This enables consistent childcare support according to the user's stage of growth and reduces the burden on parents.

[0123] "Basic information" refers to information about the user that is necessary for initial setup, such as name, date of birth, and gender.

[0124] "Movement and sound" refers to data on the newborn's body movements, cries, and other vocalizations.

[0125] The "means of collecting data" refers to the method of using a camera and microphone to monitor the newborn's movements and sounds and collecting this data on a terminal.

[0126] "Means for analyzing collected data" refers to methods for analyzing the daily rhythms and characteristics of newborns using collected data, and in particular, machine learning models are often used to perform highly accurate analysis.

[0127] The "means for providing advice" is a method for generating and notifying specific child-rearing advice to the user based on the analysis results.

[0128] "Means for detecting abnormalities" refers to a method of constantly monitoring the movements and sounds of the newborn and detecting any abnormal patterns.

[0129] "Means for making emergency contact" refers to a method for automatically sending a notification to designated contacts when an abnormality is detected.

[0130] "Means for transferring data" refers to a method for transferring data from a newborn to a new device suitable for the next stage of development.

[0131] "Machine learning model" refers to the algorithms and techniques used for analysis and modeling using collected data.

[0132] "Designated Contact" means the contact information for a parent, emergency services, or other person who should be contacted in an emergency.

[0133] Overall system configuration

[0134] This system allows users to exchange terminals as they grow, and provides consistent services while transferring data. The main elements of the system and their processing are explained below.

[0135] Enter basic information

[0136] For the initial setup, the user uses a smartphone application to enter basic information about the newborn, such as their name, date of birth, and gender. This information is then encrypted and sent from the device to a server, which stores it in a database, allowing for any necessary personalization during subsequent processes.

[0137] Data collection

[0138] The device uses a camera and microphone to monitor the newborn's movements and voice in real time. Specifically, the camera tracks the baby's position and movements, and the microphone detects crying and other sounds. This data is periodically sent to a server for real-time data collection.

[0139] Data analysis

[0140] The server analyzes the collected data. Generative AI models are used to achieve highly accurate data analysis. This analysis allows the newborn's daily rhythms and characteristics to be modeled. For example, the server analyzes the baby's sleep patterns and crying frequency to identify outliers and general trends.

[0141] Providing advice

[0142] Based on the analysis results, the server generates specific childcare advice. High-precision advice is generated using a generative AI model. For example, if a baby frequently cries at night, the server will advise the user to "play music at a steady rhythm." The device then notifies the user of this advice via a smartphone app.

[0143] Anomaly detection and emergency contact

[0144] The device monitors the newborn's movements and sounds in real time. If an abnormality is detected, the device sends the information to a server. The server analyzes the received data and determines whether it is an emergency. In the event of an emergency, an emergency notification is automatically sent to designated contacts (e.g., parents, emergency services). Users can also receive emergency notifications through a smartphone app, enabling a prompt response.

[0145] Data transfer

[0146] As the user grows, for example, when they reach the age of two, the server sends them a notification to transition to a device suitable for their new stage of development. The user purchases a new device and performs initial setup, such as Wi-Fi settings. Once the device has completed the new device setup, the server transfers all personal data to the new device. This ensures consistent support for the new device.

[0147] Examples and prompts

[0148] For example, when a user enters basic information about a newborn baby into a smartphone app, the device sends it to a server and stores it in a database. The device uses a camera and microphone to monitor the baby's movements and sounds, sending the data to the server in real time. The server analyzes the data and generates advice such as "playing music at a steady rhythm" if the baby is crying frequently at night. In an emergency, emergency services will be automatically contacted. When the user reaches a new developmental stage, the data is transferred to a new device.

[0149] Specific prompt examples:

[0150] "How to build a system that analyzes a baby's sleep patterns and generates and notifies appropriate childcare advice"

[0151] As described above, this system provides users with consistent childcare support and provides concrete measures to reduce the burden of childcare.

[0152] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0153] Step 1: Enter basic information

[0154] The user opens the application on their smartphone and enters basic information about the newborn, such as the newborn's name, date of birth, and gender. The device encrypts this information and sends it to the server, which then stores the received information in a database. The input is the newborn's basic information, such as the newborn's name, date of birth, and gender, entered by the user, and the output is that this information is accurately stored in the database.

[0155] Step 2: Collect data

[0156] The device uses a camera and microphone to monitor the newborn's movements and voice 24 hours a day. The camera captures the baby's position and movements, while the microphone collects crying and other sounds. This data is sent from the device to a server in real time. The input is the newborn's real-time movements and voice data, and the output is sent appropriately to the server.

[0157] Step 3: Analyze the data

[0158] The server analyzes the collected data. It uses a generative AI model to perform highly accurate data analysis and model the newborn's daily rhythms and characteristics. The analyzed data includes the baby's sleep patterns and crying frequency. The server uses a machine learning model to extract outliers and general trends and outputs them as the analysis results. The input is movement and audio data transmitted in real time, and the output is the modeled analysis results.

[0159] Step 4: Providing advice

[0160] The server generates specific childcare advice based on the analysis results. The advice is created using a generative AI model and notified to the user via the device. For example, if a baby frequently cries at night, the server will generate advice such as "play music at a steady rhythm." The input is the result of data analysis, and the output is a notification of specific childcare advice.

[0161] Step 5: Anomaly detection and emergency notification

[0162] The device monitors the newborn's abnormal movements and sounds in real time. If any suspicious movements are detected, the device sends the information to a server. The server analyzes the abnormal data and determines whether it is an emergency. If an emergency is determined, an emergency notification is automatically sent to designated contacts. The user can also receive the emergency notification through a smartphone application. The input is real-time data for detecting an abnormality, and the output is a notification to contact the emergency services.

[0163] Step 6: Transfer data

[0164] As the user grows, for example, when they reach the age of two, the server sends them a notification to migrate to a device suitable for their new stage of development. The user purchases a new device and performs initial setup such as Wi-Fi settings. Once the device completes the new device setup, the server migrates all personal data to the new device. This provides consistent support on the new device. The input is the migration instruction for the new device, and the output is the migrated data.

[0165] (Application example 1)

[0166] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0167] Conventional newborn monitoring systems struggle to provide appropriate devices and services for newborns as they grow. They also lack sufficient emergency response and childcare advice tailored to the newborn's development. This results in users having to purchase individual devices or use different systems, increasing the burden of childcare. Furthermore, while rapid and appropriate responses are required when an abnormality is detected, such systems are limited. An effective system that solves these problems is needed.

[0168] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0169] In this invention, the server includes means for inputting basic information about the newborn, means for monitoring the newborn's movements and voices and collecting data, means for analyzing the collected data and providing advice to the user, means for making emergency contact when an abnormality is detected, means for transferring data to the next device as the user grows, means for providing childcare advice and emergency response measures according to the newborn's stage of growth, and means for transmitting monitored data to the server in real time, thereby enabling consistent childcare support according to the newborn's stage of growth and rapid response to abnormalities.

[0170] "Replacing devices as users grow" means replacing appropriate hardware or software devices with new ones to provide the features and services required by users as they grow.

[0171] "Data transfer" refers to the consistent transfer of all personal data from an old device to a new device, ensuring that users continue to receive seamless services.

[0172] "Means for inputting basic information about a newborn" refers to a means for using a user interface such as a smartphone or computer to input initial information such as the newborn's name, date of birth, and gender, and registering it in the system.

[0173] "Means for monitoring the movements and sounds of newborns and collecting data" refers to means for using sensors such as cameras and microphones to monitor the movements and sounds of newborns in real time and collect this data.

[0174] The "means for analyzing collected data and providing advice to users" refers to means that has the function of analyzing data sent to the server, generating specific advice regarding child-rearing, and providing it to users.

[0175] "Means for making emergency contact when an abnormality is detected" refers to a means for automatically sending a notification to a designated emergency contact if an abnormality is detected in the newborn's movements or voice.

[0176] "Means for transferring data to the next device as the user grows" refers to a means for transferring all personal data to an appropriate new device as the user grows, thereby enabling uninterrupted service provision.

[0177] "Means for providing childcare advice and emergency response measures according to the user's stage of development" refers to means that have the function of automatically generating and providing appropriate childcare advice and emergency response measures according to the user's age and stage of development.

[0178] The "means for transmitting monitoring data to a server in real time" refers to a means for transmitting monitoring data of the newborn's movements and voice to a server in real time via the Internet, enabling immediate processing and analysis.

[0179] The following system and its processing will be described as an embodiment of the present invention. This system provides optimal services by replacing devices as users grow and transferring data.

[0180] Overall system configuration

[0181] The system consists of the following main components:

[0182] 1. A way to enter basic information about newborns

[0183] 2. A means of collecting data by monitoring the movements and sounds of newborns

[0184] 3. A means of analyzing collected data and providing advice to users

[0185] 4. Means of emergency contact when an abnormality is detected

[0186] 5. A way to transfer data to the next device as users grow

[0187] 6. A means of providing stage-appropriate parenting advice and emergency response plans

[0188] 7. A means of sending monitoring data to the server in real time

[0189] A means of entering basic information about a newborn

[0190] For the initial setup, the user uses a smartphone application to enter basic information about the newborn, such as their name, date of birth, and gender. The device receives this information, sends it to a server, and stores it in a database. This information forms the basis for personalization in all subsequent processes.

[0191] A means of monitoring and collecting data on newborn movements and sounds

[0192] The device uses a camera and microphone to monitor the newborn's movements and sounds 24 / 7, including the baby's crying, sleep patterns, and body movements, and the collected data is sent to a server in real time.

[0193] A means of analyzing collected data and providing advice to users

[0194] The server analyzes the collected data and models the newborn's daily rhythm and characteristics. Based on the analysis results, it generates specific childcare advice for the user. For example, if a baby frequently cries at night, the server will provide the user with advice such as "play music at a steady rhythm." The device then notifies the user of this advice via a smartphone app.

[0195] A means of making emergency contact when an abnormality is detected

[0196] The device detects any abnormal movements or sounds from the newborn. The server analyzes the abnormal data, determines whether an emergency has occurred, and automatically sends an emergency notification to designated contacts. The user receives the emergency notification via a smartphone app, allowing them to respond quickly.

[0197] A way to transfer data to the next device as users grow

[0198] When a user reaches the next growth stage, the server sends a notification to migrate to a new device. The user sets up the next device, and the device establishes the new device's Wi-Fi settings and connects to the server. The server then migrates all personal data to the new device, providing consistent support.

[0199] A means of providing stage-specific parenting advice and emergency response plans

[0200] The server generates childcare advice and emergency response measures that are tailored to the newborn's development. For example, if it detects the baby's crying, it will send an alarm to the user, telling them to "check if the baby's temperature is normal." It also provides advice on vaccination schedules and nutrition for each stage of the baby's development.

[0201] A means of sending monitoring data to a server in real time

[0202] The monitoring data is sent to a server in real time. The server immediately processes the received data and responds immediately if an abnormality occurs. This real-time processing enables prompt and appropriate childcare support.

[0203] Adding specific examples

[0204] For example, when a user enters basic information about a newborn into a smartphone app, the system sends this information to the server and stores it in a database. When the device detects the baby's crying, the server analyzes the data and sends a notification to the user, asking them to check if the baby's temperature is normal.

[0205] Example prompts to input to the generative AI model

[0206] "Generate tips on how to deal with a crying baby at night."

[0207] "Detect baby cries and provide emergency response based on that."

[0208] "Please tell me in detail how to provide first aid if a newborn baby's temperature suddenly rises."

[0209] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0210] Step 1:

[0211] The user uses a smartphone application to enter basic information such as the newborn's name, date of birth, and gender. The information entered by the user is sent from the smartphone application to the server and stored in a database. At this stage, input: basic information (name, date of birth, gender), output: basic information stored in the database. Specifically, when the user enters the required information into the application form and presses the "Submit" button, the data is sent to the server.

[0212] Step 2:

[0213] The device uses a camera and microphone to monitor the newborn's movements and voice 24 hours a day. The collected data is sent to a server in real time. Input: Newborn's movements and voice data, Output: Monitoring data sent to the server. Specifically, the device's built-in camera and microphone continuously capture video and audio, and send this data to the server via the network.

[0214] Step 3:

[0215] The server analyzes the received monitoring data and models the newborn's daily rhythms and behavioral patterns. Based on the analysis results, it generates specific child-rearing advice. Input: Monitoring data, Output: Child-rearing advice. Specifically, a data analysis algorithm runs within the server, and if the baby is crying a lot at night, for example, it generates advice such as "play music at a steady rhythm."

[0216] Step 4:

[0217] The server notifies the user of the generated parenting advice via a smartphone application. Input: Parenting advice, Output: Parenting advice displayed on the smartphone. Specifically, the server sends a notification to the user's smartphone, and the advice is displayed in the app's notification center or pop-up.

[0218] Step 5:

[0219] The device monitors the newborn's abnormal movements and sounds, and if an abnormality is detected, it immediately notifies the server. The server analyzes the abnormal data and, if it determines that there is an emergency, automatically notifies the designated emergency contacts. Input: Abnormal movement and sound data, Output: Emergency notification. Specifically, when an abnormality is detected, the device sends data to the server, and the server notifies the emergency contacts by phone or SMS.

[0220] Step 6:

[0221] When the user reaches the next growth stage, the server sends the user a notification to migrate to a new device. The user accepts and configures the new device. When the device is connected, the server migrates all personal data to the new device. Input: Information about the new device, Output: Data migrated to the new device. Specifically, the user connects the new device to Wi-Fi and sends information to the server, and the server copies the original data to the new device.

[0222] Step 7:

[0223] The server provides parenting advice tailored to the newborn's developmental stage and emergency response measures. Input: Developmental stage information, Output: Advice and response measures according to the developmental stage. Specifically, the server compares the data with past data to determine the developmental stage, generates the necessary parenting advice and emergency response measures, and notifies the app.

[0224] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0225] The following system and its processing will be described as an embodiment of the present invention. This system provides optimized services by replacing devices according to the needs of a user as they grow from newborn, while inheriting personal data. Furthermore, it includes an emotion engine that recognizes the user's emotions and adjusts advice based on those emotions.

[0226] Overall system configuration

[0227] The system consists of the following main components:

[0228] 1. A way to enter basic information about newborns

[0229] 2. A means of collecting data by monitoring the movements and sounds of newborns

[0230] 3. A means of analyzing collected data and providing advice to users

[0231] 4. Means of emergency contact when an abnormality is detected

[0232] 5. A way to transfer data to the next device as users grow

[0233] 6. Emotion engine that recognizes user emotions

[0234] 7. Means for analyzing the emotional data recognized by the emotion engine and adjusting the advice

[0235] Each element is specifically implemented as follows:

[0236] A means of entering basic information about a newborn

[0237] For the initial setup, the user uses a smartphone app to enter basic information such as the newborn's name, date of birth, and gender. The device receives this information, sends it to a server, and stores it in a database. This information forms the basis for personalization in all subsequent processes.

[0238] A means of monitoring and collecting data on newborn movements and sounds

[0239] The device uses a camera and microphone to monitor the newborn's movements and sounds 24 / 7, including the baby's crying, sleep patterns, and body movements, and the collected data is sent to a server in real time.

[0240] A means of analyzing collected data and providing advice to users

[0241] The server analyzes the collected data and models the newborn's daily rhythm and characteristics. Based on the analysis results, it generates specific childcare advice for the user. For example, if a baby frequently cries at night, the server will provide the user with advice such as "play music at a steady rhythm." The device then notifies the user of this advice via a smartphone app.

[0242] A means of making emergency contact when an abnormality is detected

[0243] The device detects abnormal movements or sounds from the newborn. The server analyzes the abnormal data, determines whether it is an emergency, and automatically sends an emergency notification to designated contacts (e.g., emergency services, parents). The user receives the emergency notification via a smartphone app, allowing them to respond quickly.

[0244] A way to transfer data to the next device as users grow

[0245] When the user turns two years old, the server sends a notification to transition to a device suitable for the next stage of development. The user purchases a new device and sets it up. The device establishes the new device's Wi-Fi settings and connects to the server. The server transfers all personal data to the new device and continues to provide consistent support.

[0246] Emotion engine that recognizes user emotions

[0247] The device uses a camera and voice recognition technology to analyze the user's facial expressions and tone of voice, and an emotion engine to recognize the user's emotions, allowing it to more accurately understand the baby's needs and discomfort.

[0248] A means of analyzing the emotional data recognized by the emotion engine and adjusting the advice

[0249] The server analyzes the emotional data collected by the emotion engine to assess the user's current emotional state. For example, if the server determines that the user is under stress, it will provide special care advice. This advice is dynamically adjusted according to the user's emotional state, enabling more personalized care.

[0250] Processing explanation in natural language with concrete examples

[0251] For example, when a user enters basic information about a newborn into a smartphone app, the device sends this information to a server and stores it in a database. The device then uses a camera and microphone to monitor the baby's movements and sounds 24 / 7. The collected data is sent to the server in real time, which analyzes it. For example, if the server detects that the baby is crying frequently at night, it will notify the user through the smartphone app with advice to "play music at a regular rhythm." Furthermore, if the device detects abnormal movements or sounds from the baby, the server will determine this is an emergency and automatically contact emergency services. Finally, when the user turns two years old, the server will transfer the data to a new device, providing consistent support for childcare.

[0252] By introducing the emotion engine, it becomes possible to more accurately grasp the baby's emotional state and provide appropriate care. For example, if the server recognizes that the baby is feeling strong anxiety in a particular situation, it will provide special advice to the user to provide a sense of security. In this way, the emotion engine realizes optimal support according to the user's emotions.

[0253] The processing flow will be explained below.

[0254] Step 1:

[0255] The user opens the smartphone app and connects the new monitoring camera device to Wi-Fi.

[0256] Step 2:

[0257] The device checks the Internet connection and performs a connection test to the server.

[0258] Step 3:

[0259] The server verifies the connection and sends the settings screen to the user.

[0260] Step 4:

[0261] The user enters basic information about the newborn baby, such as their name, date of birth, and gender, on the app's settings screen.

[0262] Step 5:

[0263] The terminal receives the information entered by the user and transmits it to the server.

[0264] Step 6:

[0265] The server stores the received information in a database.

[0266] Step 7:

[0267] The device uses a camera and microphone to monitor the newborn's movements and sounds 24 hours a day.

[0268] Step 8:

[0269] The data collected by the device is sent to the server in real time.

[0270] Step 9:

[0271] The server receives the data and performs pre-processing (noise removal, time synchronization, etc.).

[0272] Step 10:

[0273] The server analyzes the preprocessed data and models the newborn's daily rhythms and characteristics.

[0274] Step 11:

[0275] The server generates specific child-rearing advice based on the analysis results.

[0276] Step 12:

[0277] The server notifies the user of the generated advice.

[0278] Step 13:

[0279] The device displays a notification to the user via a smartphone app, saying, "The baby has started crying. Please play music."

[0280] Step 14:

[0281] The user confirms the notification and starts playing music in the app.

[0282] Step 15:

[0283] The device will play music and continue to monitor your baby's condition.

[0284] Step 16:

[0285] The device detects abnormal movements or sounds from the baby.

[0286] Step 17:

[0287] Any abnormality information detected by the device is immediately sent to the server.

[0288] Step 18:

[0289] The server analyzes the abnormal data and determines whether it is an emergency.

[0290] Step 19:

[0291] If the server determines that an emergency exists, it will automatically send an emergency notification to the designated contacts.

[0292] Step 20:

[0293] The device sends an emergency notification to the user, displaying the message "Your baby is in danger. Call an ambulance."

[0294] Step 21:

[0295] Users can check emergency notifications and take appropriate action immediately.

[0296] Step 22:

[0297] The server sends a notification to the user to transition to a new device when the user turns two years old.

[0298] Step 23:

[0299] The device will display a message saying "Please move to the next stage device" and provide guidelines.

[0300] Step 24:

[0301] A user purchases a new device and sets it up for initial setup.

[0302] Step 25:

[0303] The device establishes a Wi-Fi connection for the new device and connects to the server.

[0304] Step 26:

[0305] The server will transfer all existing data to the new device.

[0306] Step 27:

[0307] The device receives the migrated data and starts new support tailored to the growing user base.

[0308] Step 28:

[0309] The server analyzes the monitoring data from the new device and continues to provide consistent parenting support.

[0310] Step 29:

[0311] The device uses a camera and microphone to collect the user's facial expressions and tone of voice.

[0312] Step 30:

[0313] The data collected by the device is sent to the server in real time.

[0314] Step 31:

[0315] The server uses an emotion engine to analyze the collected data and recognize the user's emotional state.

[0316] Step 32:

[0317] The server adjusts the parenting advice based on the emotional data.

[0318] Step 33:

[0319] The server notifies the user of the adjusted advice.

[0320] Step 34:

[0321] The device displays a message via a smartphone app saying, "Your baby seems anxious. Please hold him."

[0322] Step 35:

[0323] The user sees the notification and takes the appropriate action.

[0324] Example 2

[0325] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0326] Modern childcare demands personalized services that meet the needs of children from newborn to adulthood. However, conventional systems have struggled to provide services while consistently transferring data and replacing devices appropriately as users grow. Recognizing users' emotions and providing appropriate advice is also a challenge. Furthermore, systems lacked the ability to quickly and automatically contact emergency personnel when an abnormality was detected.

[0327] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0328] In this invention, the server includes means for inputting basic information about the user, means for collecting data by monitoring the user's movements and voice, means for analyzing the collected data and providing advice to the user, means for making emergency contact when an abnormality is detected, means for transferring data to a subsequent device in accordance with the user's growth, an emotion engine for recognizing the user's emotions, and means for analyzing the emotion data recognized by the emotion engine and adjusting advice. This enables device replacement and data transfer in accordance with the user's growth, provision of personalized services based on emotions, and rapid emergency response.

[0329] The term "user" refers to a person who uses the system, and in the present invention refers to all users including newborns and their growing children.

[0330] The term "device" refers to all hardware devices used in the system of the present invention, including monitoring devices, recording devices, communication devices, and the like.

[0331] "Basic Information" refers to the default information about a User, including personally identifiable information such as name, date of birth, and gender.

[0332] "Means for monitoring movements and sounds" refers to the function of recording and collecting user actions and sounds in real time using input devices such as cameras and microphones.

[0333] "Data collection means" means any process or device that temporarily or permanently stores information such as a user's movements or voice.

[0334] "Means for analyzing data" refers to functions, including software and algorithms, that analyze collected data and identify specific patterns or trends.

[0335] "Means for providing advice" means a system function for making suggestions to users regarding childcare and health management based on the analysis results.

[0336] "Means for making emergency contact" refers to the function of promptly sending warnings or notifications to the user or designated third parties via communication means when an abnormality is detected.

[0337] "Means for transferring data" refers to the ability to transfer data from an old device to a new device as the user grows.

[0338] "Emotion-aware emotion engine" means specialized algorithms and software that analyze a user's facial expressions and tone of voice to recognize their emotional state.

[0339] "Means for analyzing emotional data and adjusting advice" refers to the function of appropriately adjusting the content of advice based on emotional data recognized by the emotion engine, thereby providing a more personalized service.

[0340] The system of the present invention aims to provide personalized services through device replacement, data transfer, and emotion recognition in accordance with the user's growth. This system is composed of multiple hardware and software components, the role of which is described in detail below.

[0341] Overall system configuration

[0342] The system consists of the following main components:

[0343] 1. A way to enter basic user information

[0344] 2. Collecting data by monitoring your movements and voice

[0345] 3. A means of analyzing collected data and providing advice to users

[0346] 4. Means of emergency contact when an abnormality is detected

[0347] 5. A way to transfer data to the next device as the user grows

[0348] 6. Emotion engine that recognizes user emotions

[0349] 7. Means for analyzing the emotional data recognized by the emotion engine and adjusting the advice

[0350] A means of entering basic user information

[0351] For initial setup, the user uses a smartphone application to enter basic information such as the user's name, date of birth, gender, etc. The device receives this information, sends it to the server, and stores it in a database. This information forms the basis for personalization in all subsequent processes.

[0352] A means of collecting data by monitoring user movements and voices

[0353] The device uses a camera and microphone to monitor the user's movements and voice 24 / 7, including movement patterns, tone of voice, facial expressions, etc. The collected data is sent to a server in real time.

[0354] A means of analyzing collected data and providing advice to users

[0355] The server analyzes the collected data and models the user's lifestyle and characteristics. Based on the analysis results, it generates specific advice for the user. For example, if the server recognizes that the user is feeling stressed, it will provide the advice "listen to music to relax." The device then notifies the user of this advice via a smartphone application.

[0356] A means of making emergency contact when an abnormality is detected

[0357] The device detects the user's abnormal movements or sounds. The server analyzes the abnormal data, determines that it is an emergency, and automatically sends an emergency notification to designated contacts (e.g., emergency contacts). The user receives the emergency notification through a smartphone application and can respond quickly.

[0358] A way to transfer data to the next device as the user grows

[0359] As a user grows, the server sends a migration notification to a device suitable for the next stage of growth. The user purchases a new device and performs initial setup. The device establishes the network settings for the new device and connects to the server. The server migrates all data to the new device and continues to provide consistent support.

[0360] Emotion engine that recognizes user emotions

[0361] The device uses a camera and voice recognition technology to analyze the user's facial expressions and tone of voice, and an emotion engine to recognize the user's emotions, allowing it to more accurately understand the user's needs and complaints.

[0362] A means of analyzing the emotional data recognized by the emotion engine and adjusting the advice

[0363] The server analyzes the emotion data collected by the emotion engine to assess the user's current emotional state. For example, if the server determines that the user is under stress, it provides special care advice. This advice is dynamically adjusted according to the user's emotional state, enabling more personalized care.

[0364] Processing explanation in natural language with concrete examples

[0365] For example, when a user enters basic information about a newborn into a smartphone app, the device sends this information to a server and stores it in a database. The device then uses a camera and microphone to monitor the baby's movements and sounds 24 / 7. The collected data is sent to the server in real time, which analyzes it. For example, if the server detects that the baby is crying frequently at night, it will notify the user through the smartphone app with advice to "play music at a regular rhythm." Furthermore, if the device detects abnormal movements or sounds from the baby, the server will determine this is an emergency and automatically contact emergency services. Finally, when the user turns two years old, the server will transfer the data to a new device, providing consistent childcare support.

[0366] Example prompts for generative AI models

[0367] "When a user uses a smartphone app to enter basic information about a newborn baby, please explain the specific processing steps of how that information is sent to the server and stored in the database."

[0368] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0369] Step 1:

[0370] The user launches a smartphone application and enters basic information about the newborn baby. The entered basic information includes the baby's name, date of birth, and gender. This information is collected within the application and sent to the device. The device converts this information into JSON format and sends it to the server using the HTTPS protocol. The server saves the received data in a database and returns a save completion response to the device.

[0371] Specific operation:

[0372] 1. The user opens the app's input form and enters the newborn's information.

[0373] 2. The device serializes the user input data into JSON.

[0374] 3. The device sends data to the server via HTTPS.

[0375] 4. The server validates the incoming data and saves it as a new record in the database.

[0376] 5. The server returns a save completion response to the terminal, and the terminal notifies the user.

[0377] Step 2:

[0378] The device monitors the user's movements and voice 24 / 7 using a camera and microphone. This monitoring captures the user's movement and voice patterns. This data is stored in a buffer at regular intervals and then securely transmitted to a server using a VPN.

[0379] Specific operation:

[0380] 1. The device begins capturing real-time data using the camera and microphone.

[0381] 2. Movement and audio data are temporarily stored in a buffer.

[0382] 3. At regular intervals, the contents of the buffer are sent to the server via VPN.

[0383] Step 3:

[0384] The server analyzes the received data and models the user's lifestyle and characteristics. The received data is processed by an analysis module to extract specific patterns and trends. This generates a user behavior model that is stored in a database.

[0385] Specific operation:

[0386] 1. The server passes the received data to a dedicated module that analyzes it.

[0387] 2. The analytics module runs algorithms that identify behavioral patterns and trends.

[0388] 3. Identified patterns and trends are modeled and stored in a database.

[0389] Step 4:

[0390] The server generates advice for the user based on the analysis results. The generated advice is notified to the user via a smartphone application. For example, if the server recognizes that the user is feeling stressed, it will provide the advice "listen to music to relax."

[0391] Specific operation:

[0392] 1. The server selects an advice template based on the analysis results.

[0393] 2. A specific message is generated based on the selected template.

[0394] 3. The generated advice is sent to the device, which then notifies the user via an app notification.

[0395] Step 5:

[0396] The device runs an algorithm to detect abnormal user movements or sounds. If an abnormality is detected, it sends an alert to the server. The server analyzes the alert data and, if an abnormality is detected, sends a notification to designated emergency contacts. The user receives the emergency notification through a smartphone application.

[0397] Specific operation:

[0398] 1. The device runs an anomaly detection algorithm that monitors real-time data.

[0399] 2. If an abnormality is detected, an alert is sent to the server immediately.

[0400] 3. The server analyzes the alert and, if it determines that there is an abnormality, sends a notification to the registered emergency contact.

[0401] 4. Users receive emergency notifications through the app and respond quickly.

[0402] Step 6:

[0403] The server sends migration notifications to new devices as users grow. The user purchases a new device and performs initial setup. The device establishes network settings for the new device and connects to the server. The server migrates all data to the new device and continues to provide consistent support.

[0404] Specific operation:

[0405] 1. The server monitors the user's growth data and generates migration notifications at appropriate times.

[0406] 2. The user purchases a new device and goes through the initial setup procedure.

[0407] 3. The device completes the network configuration of the new device and connects to the server.

[0408] 4. The server transfers the data from the old device to the new device.

[0409] Step 7:

[0410] The device uses a camera and voice recognition technology to analyze the user's facial expressions and tone of voice, and recognizes the user's emotions using an emotion engine. This data is sent to a server, which then analyzes it using the emotion engine. Based on the analysis results, tailored advice is provided to the user.

[0411] Specific operation:

[0412] 1. The device uses a camera and microphone to perform facial recognition and voice analysis.

[0413] 2. The analyzed data is sent to the server in real time.

[0414] 3. The server passes the data to the emotion engine to evaluate the user's emotional state.

[0415] 4. Based on the evaluation results, generate and notify tailored advice to the user.

[0416] (Application example 2)

[0417] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0418] While modern childcare demands personalized support tailored to each newborn's developmental stage, manual information management and decision-making are required, increasing the burden of childcare. It is also difficult to accurately grasp a newborn's emotional state and provide appropriate care based on that. Furthermore, childcare products and services are typically offered in brick-and-mortar stores, lacking personalization tailored to individual needs. This often results in inadequate childcare support.

[0419] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for inputting basic information about the newborn, a means for monitoring the newborn's movements and voice to collect data, a means for analyzing the collected data and providing advice to the user, a means for making an emergency call when an abnormality is detected, a means for recognizing the user's emotions and adjusting advice based on the emotion data, a means for transferring data to the next device as the user grows, and a means for proposing personalized products and services in physical stores and providing special care counseling. This enables seamless childcare support according to the newborn's growth stage, provision of appropriate care based on the newborn's emotional state, consistent data management, and provision of personalized services in physical stores according to individual needs.

[0420] "Means for inputting basic information about a newborn" is a function that allows a user to input basic information about a newborn, such as the name, date of birth, and gender, and send it to the server.

[0421] "Means for monitoring the movements and sounds of newborns and collecting data" refers to a function that uses cameras and microphones to monitor the movements and sounds of newborns 24 hours a day and collect data.

[0422] "Means for analyzing collected data and providing advice to users" refers to a function in which the server analyzes collected data, models the daily rhythms and characteristics of the newborn, and provides appropriate child-rearing advice to users.

[0423] "Means for making emergency contact when an abnormality is detected" is a function that allows the system to detect abnormal movements or sounds from the newborn and automatically notify emergency contacts.

[0424] "Means for recognizing the user's emotions and adjusting advice based on emotional data" refers to a function that uses an emotion engine to analyze the user's facial expressions and tone of voice and adjust advice to provide appropriate care.

[0425] "A way to transfer data to the next device as the user grows" is a feature that allows existing data to be transferred to a new device as the newborn grows, providing consistent parenting support.

[0426] "Means of proposing personalized products and services in physical stores and providing special care counseling" refers to a function that personalizes the proposal of childcare products and services in physical stores and provides care counseling according to individual needs.

[0427] The following system and its processing will be described as an embodiment of the present invention. This system provides optimized services by replacing devices according to the needs of a user as they grow from newborn, while inheriting personal data. Furthermore, it includes an emotion engine that recognizes the user's emotions and adjusts advice based on those emotions.

[0428] Overall system configuration

[0429] The system consists of the following main components:

[0430] 1. A way to enter basic information about newborns

[0431] 2. A means of collecting data by monitoring the movements and sounds of newborns

[0432] 3. A means of analyzing collected data and providing advice to users

[0433] 4. Means of emergency contact when an abnormality is detected

[0434] 5. A way to recognize user emotions and tailor recommendations based on emotional data

[0435] 6. A way to transfer data to the next device as users grow

[0436] 7. A way to offer personalized products and services in physical stores and provide special care counseling

[0437] A means of entering basic information about a newborn

[0438] For the initial setup, the user uses a smartphone app to enter basic information about the newborn, such as their name, date of birth, and gender. The device receives this information, sends it to a server, and stores it in a database. This information forms the basis for personalization in all subsequent processes.

[0439] A means of monitoring and collecting data on newborn movements and sounds

[0440] The device uses a camera and microphone to monitor the newborn's movements and sounds 24 / 7, including the baby's crying, sleep patterns, and body movements, and the collected data is sent to a server in real time.

[0441] A means of analyzing collected data and providing advice to users

[0442] The server analyzes the collected data and models the newborn's daily rhythm and characteristics. Based on the analysis results, it generates specific childcare advice for the user. For example, if a baby frequently cries at night, the server will provide the user with advice such as "play music at a steady rhythm." The device then notifies the user of this advice via a smartphone app.

[0443] A means of making emergency contact when an abnormality is detected

[0444] The device detects abnormal movements or sounds from the newborn. The server analyzes the abnormal data, determines whether it is an emergency, and automatically sends an emergency notification to designated contacts (e.g., ambulance, parents). The user receives the emergency notification through a smartphone app and can respond quickly.

[0445] A means of recognizing user emotions and tailoring advice based on emotional data

[0446] The device uses a camera and voice recognition technology to analyze the user's facial expressions and tone of voice, and recognizes the user's emotions using an emotion engine. This allows for more accurate understanding of the baby's needs and ailments. The server analyzes the emotion data collected by the emotion engine and evaluates the user's current emotional state. For example, if the server determines that the user is under stress, it will provide special care advice. This advice is dynamically adjusted according to the user's emotional state, enabling more personalized care.

[0447] A way to transfer data to the next device as users grow

[0448] When the user turns two years old, the server sends a notification to transition to a device suitable for the next stage of development. The user purchases a new device and sets it up. The device establishes the new device's Wi-Fi settings and connects to the server. The server transfers all personal data to the new device and continues to provide consistent support.

[0449] A means to offer personalized products and services in physical stores and provide special care counseling

[0450] There is a smartphone app that provides childcare products and services in brick-and-mortar stores, and the server proposes personalized products and services based on basic information about the newborn, their daily movements, and emotional data. The app also allows users to make reservations for care counseling sessions in brick-and-mortar stores and receive consultations in real time.

[0451] Specific examples

[0452] For example, when a user enters basic information about a newborn baby into a smartphone app, the device sends this information to a server and stores it in a database. The device then uses a camera and microphone to monitor the baby's movements and sounds 24 hours a day. The collected data is sent in real time to the server, which analyzes it. For example, if the server detects that the baby is crying frequently at night, it will notify the user through the smartphone app with advice to "play music at a regular rhythm."

[0453] By introducing the emotion engine, it becomes possible to more accurately grasp the baby's emotional state and provide appropriate care. For example, if the server recognizes that the baby is feeling strong anxiety in a particular situation, it will provide special advice to the user to provide a sense of security. In this way, the emotion engine realizes optimal support according to the user's emotions.

[0454] Example prompts for generative AI models

[0455] Generate the best advice for your crying baby based on the following data:

[0456] Basic information: Name "Newborn A", Date of birth "2022-01-01", Gender "Male"

[0457] Movement and sound data: "Frequent crying at night"

[0458] Emotion data: "crying face" and "anxious voice"

[0459] Output formats:

[0460] Advice: New Instructions

[0461] Additional Care Suggestions: Special Care Suggestions

[0462] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0463] Step 1:

[0464] The user enters basic information about the newborn into a smartphone app.

[0465] How it works: The user uses the app's input form to enter the newborn's name, date of birth, and gender, and the information is sent by the device to the server and stored in a database.

[0466] Input: Newborn's name, date of birth, sex

[0467] Output: Basic information of the newborn stored in the database

[0468] Step 2:

[0469] The device uses a camera and microphone to monitor the newborn's movements and sounds and collect data.

[0470] How it works: The device periodically activates the camera and microphone to monitor the newborn's movements and cries, and the collected data is sent to the server in real time.

[0471] Input: Video and audio data from the camera and microphone

[0472] Output: Monitoring data of the newborn's movements and voices sent to a server

[0473] Step 3:

[0474] The server analyzes the collected data and models the newborn's daily rhythms and characteristics.

[0475] How it works: The server analyzes the received data using machine learning algorithms to identify the time of day when the newborn is crying and their movement patterns.

[0476] Input: Neonatal movement and voice monitoring data

[0477] Output: Data modeling the daily rhythms and characteristics of newborns

[0478] Step 4:

[0479] The server generates parenting advice based on the analysis results and notifies the user via the device.

[0480] Specific operation: Based on the analysis data, the server creates parenting advice, such as "play music at a steady rhythm," and notifies the user via a smartphone app.

[0481] Input: Data modeling the daily rhythms and characteristics of newborns

[0482] Output: Parenting advice sent to a smartphone app

[0483] Step 5:

[0484] If the device detects any abnormal movements or sounds from the newborn, the server will automatically send an emergency notification.

[0485] Specific operation: When the device detects an abnormality, it sends the data to the server, which determines it is an emergency and automatically sends a notification to pre-defined emergency contacts.

[0486] Input: Unusual movement and audio data

[0487] Output:Notify emergency contacts

[0488] Step 6:

[0489] The device uses a camera and voice recognition technology to collect the user's emotional data, which is then analyzed by the server to tailor the advice.

[0490] How it works: The device uses a camera to capture the user's facial expressions and a microphone to analyze the tone of voice. The collected emotional data is sent to the server, which then adjusts the advice based on the user's emotional state.

[0491] Input: Emotion data from camera and microphone

[0492] Output: Advice based on emotional state

[0493] Step 7:

[0494] As the user grows, the server sends a notification for the next device migration and transfers the data to the new device.

[0495] What it does: When a user purchases and sets up a new device, the device establishes the device's Wi-Fi settings and connects to the server, which then transfers all personal data to the new device.

[0496] Input: New device setup information

[0497] Output: Personal data transferred to new device

[0498] Step 8:

[0499] Servers will suggest personalized products and services in physical stores and provide special care counseling.

[0500] How it works: The server recommends optimal products and services at physical stores based on the newborn's basic information, daily movements, and emotional data. The app also allows users to make appointments for special care counseling.

[0501] Input: Basic information of newborn baby, movement and voice data, emotion data

[0502] Output: Personalized recommendations and care counseling in physical stores

[0503] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0504] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0505] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0506] [Second embodiment]

[0507] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0508] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0509] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0510] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0511] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0512] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0513] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0514] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0515] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0516] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0517] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0518] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0519] The following system and its processing will be described as an embodiment of the present invention. This system provides optimized services by replacing devices according to the needs of users growing from newborns, while inheriting personal data.

[0520] Overall system configuration

[0521] The system consists of the following main components:

[0522] 1. A way to enter basic information about newborns

[0523] 2. A means of collecting data by monitoring the movements and sounds of newborns

[0524] 3. A means of analyzing collected data and providing advice to users

[0525] 4. Means of emergency contact when an abnormality is detected

[0526] 5. A way to transfer data to the next device as users grow

[0527] Each element is specifically implemented as follows:

[0528] A means of entering basic information about a newborn

[0529] For the initial setup, the user uses a smartphone app to enter basic information such as the newborn's name, date of birth, and gender. The device receives this information, sends it to a server, and stores it in a database. This information forms the basis for personalization in all subsequent processes.

[0530] A means of monitoring and collecting data on newborn movements and sounds

[0531] The device uses a camera and microphone to monitor the newborn's movements and sounds 24 / 7, including the baby's crying, sleep patterns, and body movements, and the collected data is sent to a server in real time.

[0532] A means of analyzing collected data and providing advice to users

[0533] The server analyzes the collected data and models the newborn's daily rhythm and characteristics. Based on the analysis results, it generates specific childcare advice for the user. For example, if a baby frequently cries at night, the server will provide the user with advice such as "play music at a steady rhythm." The device then notifies the user of this advice via a smartphone app.

[0534] A means of making emergency contact when an abnormality is detected

[0535] The device detects abnormal movements or sounds from the newborn. The server analyzes the abnormal data, determines whether it is an emergency, and automatically sends an emergency notification to designated contacts (e.g., emergency services, parents). The user receives the emergency notification via a smartphone app, allowing them to respond quickly.

[0536] A way to transfer data to the next device as users grow

[0537] When the user turns two years old, the server sends a notification to transition to a device suitable for the next stage of development. The user purchases a new device and sets it up. The device establishes the new device's Wi-Fi settings and connects to the server. The server transfers all personal data to the new device and continues to provide consistent support.

[0538] Processing explanation in natural language with concrete examples

[0539] For example, when a user enters basic information about a newborn into a smartphone app, the device sends this information to a server and stores it in a database. The device then uses a camera and microphone to monitor the baby's movements and sounds 24 / 7. The collected data is sent to the server in real time, which analyzes it. For example, if the server detects that the baby is crying frequently at night, it will notify the user through the smartphone app with advice to "play music at a regular rhythm." Furthermore, if the device detects abnormal movements or sounds from the baby, the server will determine this is an emergency and automatically contact emergency services. Finally, when the user turns two years old, the server will transfer the data to a new device, providing consistent support for childcare.

[0540] This allows users to receive consistent support as their child grows from birth, reducing the burden of childcare.

[0541] The processing flow will be explained below.

[0542] Step 1:

[0543] The user opens the smartphone app and connects the new monitoring camera device to Wi-Fi.

[0544] Step 2:

[0545] The device checks the Internet connection and performs a connection test to the server.

[0546] Step 3:

[0547] The server verifies the connection and sends the settings screen to the user.

[0548] Step 4:

[0549] The user enters basic information about the newborn baby, such as their name, date of birth, and gender, on the app's settings screen.

[0550] Step 5:

[0551] The terminal receives the information entered by the user and transmits it to the server.

[0552] Step 6:

[0553] The server stores the received information in a database.

[0554] Step 7:

[0555] The device uses a camera and microphone to monitor the newborn's movements and sounds 24 hours a day.

[0556] Step 8:

[0557] The data collected by the device is sent to the server in real time.

[0558] Step 9:

[0559] The server receives the data and performs pre-processing (noise removal, time synchronization, etc.).

[0560] Step 10:

[0561] The server analyzes the preprocessed data and models the newborn's daily rhythms and characteristics.

[0562] Step 11:

[0563] The server generates specific child-rearing advice based on the analysis results.

[0564] Step 12:

[0565] The server notifies the user of the generated advice.

[0566] Step 13:

[0567] The device displays a notification to the user via a smartphone app, saying, "The baby has started crying. Please play music."

[0568] Step 14:

[0569] The user confirms the notification and starts playing music in the app.

[0570] Step 15:

[0571] The device will play music and continue to monitor your baby's condition.

[0572] Step 16:

[0573] The device detects abnormal movements or sounds from the baby.

[0574] Step 17:

[0575] Any abnormality information detected by the device is immediately sent to the server.

[0576] Step 18:

[0577] The server analyzes the abnormal data and determines whether it is an emergency.

[0578] Step 19:

[0579] If the server determines that an emergency exists, it will automatically send an emergency notification to the designated contacts.

[0580] Step 20:

[0581] The device sends an emergency notification to the user, displaying the message "Your baby is in danger. Call an ambulance."

[0582] Step 21:

[0583] Users can check emergency notifications and take appropriate action immediately.

[0584] Step 22:

[0585] The server sends a notification to the user to transition to a new device when the user turns two years old.

[0586] Step 23:

[0587] The device will display a message saying "Please move to the next stage device" and provide guidelines.

[0588] Step 24:

[0589] A user purchases a new device and sets it up for initial setup.

[0590] Step 25:

[0591] The device establishes a Wi-Fi connection for the new device and connects to the server.

[0592] Step 26:

[0593] The server will transfer all existing data to the new device.

[0594] Step 27:

[0595] The device receives the migrated data and starts new support tailored to the growing user base.

[0596] Step 28:

[0597] The server analyzes the monitoring data from the new device and continues to provide consistent parenting support.

[0598] Example 1

[0599] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0600] Conventional childcare support systems have the problem of making it difficult to properly replace devices and transfer data as the baby grows from birth. Furthermore, data collection, analysis, and advice provision of newborn movements and voices are often inconsistent, making it difficult to respond quickly in emergencies. This creates the problem of parents being unable to receive consistent childcare support and increasing the burden of childcare on parents.

[0601] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0602] In this invention, the server includes means for inputting basic information, means for monitoring movements and sounds and collecting data, means for analyzing the collected data and providing advice, means for making emergency contact when an abnormality is detected, means for transferring data to the next device as the user grows, means for analyzing the collected data using a machine learning model and modeling daily rhythms and characteristics, and means for automatically making emergency contact and notifying designated contacts. This enables consistent childcare support according to the user's stage of growth and reduces the burden on parents.

[0603] "Basic information" refers to information about the user that is necessary for initial setup, such as name, date of birth, and gender.

[0604] "Movement and sound" refers to data on the newborn's body movements, cries, and other vocalizations.

[0605] The "means of collecting data" refers to the method of using a camera and microphone to monitor the newborn's movements and sounds and collecting this data on a terminal.

[0606] "Means for analyzing collected data" refers to methods for analyzing the daily rhythms and characteristics of newborns using collected data, and in particular, machine learning models are often used to perform highly accurate analysis.

[0607] The "means for providing advice" is a method for generating and notifying specific child-rearing advice to the user based on the analysis results.

[0608] "Means for detecting abnormalities" refers to a method of constantly monitoring the movements and sounds of the newborn and detecting any abnormal patterns.

[0609] "Means for making emergency contact" refers to a method for automatically sending a notification to designated contacts when an abnormality is detected.

[0610] "Means for transferring data" refers to a method for transferring data from a newborn to a new device suitable for the next stage of development.

[0611] "Machine learning model" refers to the algorithms and techniques used for analysis and modeling using collected data.

[0612] "Designated Contact" means the contact information for a parent, emergency services, or other person who should be contacted in an emergency.

[0613] Overall system configuration

[0614] This system allows users to exchange terminals as they grow, and provides consistent services while transferring data. The main elements of the system and their processing are explained below.

[0615] Enter basic information

[0616] For the initial setup, the user uses a smartphone application to enter basic information about the newborn, such as their name, date of birth, and gender. This information is then encrypted and sent from the device to a server, which stores it in a database, allowing for any necessary personalization during subsequent processes.

[0617] Data collection

[0618] The device uses a camera and microphone to monitor the newborn's movements and voice in real time. Specifically, the camera tracks the baby's position and movements, and the microphone detects crying and other sounds. This data is periodically sent to a server for real-time data collection.

[0619] Data analysis

[0620] The server analyzes the collected data. Generative AI models are used to achieve highly accurate data analysis. This analysis allows the newborn's daily rhythms and characteristics to be modeled. For example, the server analyzes the baby's sleep patterns and crying frequency to identify outliers and general trends.

[0621] Providing advice

[0622] Based on the analysis results, the server generates specific childcare advice. High-precision advice is generated using a generative AI model. For example, if a baby frequently cries at night, the server will advise the user to "play music at a steady rhythm." The device then notifies the user of this advice via a smartphone app.

[0623] Anomaly detection and emergency contact

[0624] The device monitors the newborn's movements and sounds in real time. If an abnormality is detected, the device sends the information to a server. The server analyzes the received data and determines whether it is an emergency. In the event of an emergency, an emergency notification is automatically sent to designated contacts (e.g., parents, emergency services). Users can also receive emergency notifications through a smartphone app, enabling a prompt response.

[0625] Data transfer

[0626] As the user grows, for example, when they reach the age of two, the server sends them a notification to transition to a device suitable for their new stage of development. The user purchases a new device and performs initial setup, such as Wi-Fi settings. Once the device has completed the new device setup, the server transfers all personal data to the new device. This ensures consistent support for the new device.

[0627] Examples and prompts

[0628] For example, when a user enters basic information about a newborn baby into a smartphone app, the device sends it to a server and stores it in a database. The device uses a camera and microphone to monitor the baby's movements and sounds, sending the data to the server in real time. The server analyzes the data and generates advice such as "playing music at a steady rhythm" if the baby is crying frequently at night. In an emergency, emergency services will be automatically contacted. When the user reaches a new developmental stage, the data is transferred to a new device.

[0629] Specific prompt examples:

[0630] "How to build a system that analyzes a baby's sleep patterns and generates and notifies appropriate childcare advice"

[0631] As described above, this system provides users with consistent childcare support and provides concrete measures to reduce the burden of childcare.

[0632] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0633] Step 1: Enter basic information

[0634] The user opens the application on their smartphone and enters basic information about the newborn, such as the newborn's name, date of birth, and gender. The device encrypts this information and sends it to the server, which then stores the received information in a database. The input is the newborn's basic information, such as the newborn's name, date of birth, and gender, entered by the user, and the output is that this information is accurately stored in the database.

[0635] Step 2: Collect data

[0636] The device uses a camera and microphone to monitor the newborn's movements and voice 24 hours a day. The camera captures the baby's position and movements, while the microphone collects crying and other sounds. This data is sent from the device to a server in real time. The input is the newborn's real-time movements and voice data, and the output is sent appropriately to the server.

[0637] Step 3: Analyze the data

[0638] The server analyzes the collected data. It uses a generative AI model to perform highly accurate data analysis and model the newborn's daily rhythms and characteristics. The analyzed data includes the baby's sleep patterns and crying frequency. The server uses a machine learning model to extract outliers and general trends and outputs them as the analysis results. The input is movement and audio data transmitted in real time, and the output is the modeled analysis results.

[0639] Step 4: Providing advice

[0640] The server generates specific childcare advice based on the analysis results. The advice is created using a generative AI model and notified to the user via the device. For example, if a baby frequently cries at night, the server will generate advice such as "play music at a steady rhythm." The input is the result of data analysis, and the output is a notification of specific childcare advice.

[0641] Step 5: Anomaly detection and emergency notification

[0642] The device monitors the newborn's abnormal movements and sounds in real time. If any suspicious movements are detected, the device sends the information to a server. The server analyzes the abnormal data and determines whether it is an emergency. If an emergency is determined, an emergency notification is automatically sent to designated contacts. The user can also receive the emergency notification through a smartphone application. The input is real-time data for detecting an abnormality, and the output is a notification to contact the emergency services.

[0643] Step 6: Transfer data

[0644] As the user grows, for example, when they reach the age of two, the server sends them a notification to migrate to a device suitable for their new stage of development. The user purchases a new device and performs initial setup such as Wi-Fi settings. Once the device completes the new device setup, the server migrates all personal data to the new device. This provides consistent support on the new device. The input is the migration instruction for the new device, and the output is the migrated data.

[0645] (Application example 1)

[0646] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0647] Conventional newborn monitoring systems struggle to provide appropriate devices and services for newborns as they grow. They also lack sufficient emergency response and childcare advice tailored to the newborn's development. This results in users having to purchase individual devices or use different systems, increasing the burden of childcare. Furthermore, while rapid and appropriate responses are required when an abnormality is detected, such systems are limited. An effective system that solves these problems is needed.

[0648] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0649] In this invention, the server includes means for inputting basic information about the newborn, means for monitoring the newborn's movements and voices and collecting data, means for analyzing the collected data and providing advice to the user, means for making emergency contact when an abnormality is detected, means for transferring data to the next device as the user grows, means for providing childcare advice and emergency response measures according to the newborn's stage of growth, and means for transmitting monitored data to the server in real time, thereby enabling consistent childcare support according to the newborn's stage of growth and rapid response to abnormalities.

[0650] "Replacing devices as users grow" means replacing appropriate hardware or software devices with new ones to provide the features and services required by users as they grow.

[0651] "Data transfer" refers to the consistent transfer of all personal data from an old device to a new device, ensuring that users continue to receive seamless services.

[0652] "Means for inputting basic information about a newborn" refers to a means for using a user interface such as a smartphone or computer to input initial information such as the newborn's name, date of birth, and gender, and registering it in the system.

[0653] "Means for monitoring the movements and sounds of newborns and collecting data" refers to means for using sensors such as cameras and microphones to monitor the movements and sounds of newborns in real time and collect this data.

[0654] The "means for analyzing collected data and providing advice to users" refers to means that has the function of analyzing data sent to the server, generating specific advice regarding child-rearing, and providing it to users.

[0655] "Means for making emergency contact when an abnormality is detected" refers to a means for automatically sending a notification to a designated emergency contact if an abnormality is detected in the newborn's movements or voice.

[0656] "Means for transferring data to the next device as the user grows" refers to a means for transferring all personal data to an appropriate new device as the user grows, thereby enabling uninterrupted service provision.

[0657] "Means for providing childcare advice and emergency response measures according to the user's stage of development" refers to means that have the function of automatically generating and providing appropriate childcare advice and emergency response measures according to the user's age and stage of development.

[0658] The "means for transmitting monitoring data to a server in real time" refers to a means for transmitting monitoring data of the newborn's movements and voice to a server in real time via the Internet, enabling immediate processing and analysis.

[0659] The following system and its processing will be described as an embodiment of the present invention. This system provides optimal services by replacing devices as users grow and transferring data.

[0660] Overall system configuration

[0661] The system consists of the following main components:

[0662] 1. A way to enter basic information about newborns

[0663] 2. A means of collecting data by monitoring the movements and sounds of newborns

[0664] 3. A means of analyzing collected data and providing advice to users

[0665] 4. Means of emergency contact when an abnormality is detected

[0666] 5. A way to transfer data to the next device as users grow

[0667] 6. A means of providing stage-appropriate parenting advice and emergency response plans

[0668] 7. A means of sending monitoring data to the server in real time

[0669] A means of entering basic information about a newborn

[0670] For the initial setup, the user uses a smartphone application to enter basic information about the newborn, such as their name, date of birth, and gender. The device receives this information, sends it to a server, and stores it in a database. This information forms the basis for personalization in all subsequent processes.

[0671] A means of monitoring and collecting data on newborn movements and sounds

[0672] The device uses a camera and microphone to monitor the newborn's movements and sounds 24 / 7, including the baby's crying, sleep patterns, and body movements, and the collected data is sent to a server in real time.

[0673] A means of analyzing collected data and providing advice to users

[0674] The server analyzes the collected data and models the newborn's daily rhythm and characteristics. Based on the analysis results, it generates specific childcare advice for the user. For example, if a baby frequently cries at night, the server will provide the user with advice such as "play music at a steady rhythm." The device then notifies the user of this advice via a smartphone app.

[0675] A means of making emergency contact when an abnormality is detected

[0676] The device detects any abnormal movements or sounds from the newborn. The server analyzes the abnormal data, determines whether an emergency has occurred, and automatically sends an emergency notification to designated contacts. The user receives the emergency notification via a smartphone app, allowing them to respond quickly.

[0677] A way to transfer data to the next device as users grow

[0678] When a user reaches the next growth stage, the server sends a notification to migrate to a new device. The user sets up the next device, and the device establishes the new device's Wi-Fi settings and connects to the server. The server then migrates all personal data to the new device, providing consistent support.

[0679] A means of providing stage-specific parenting advice and emergency response plans

[0680] The server generates childcare advice and emergency response measures that are tailored to the newborn's development. For example, if it detects the baby's crying, it will send an alarm to the user, telling them to "check if the baby's temperature is normal." It also provides advice on vaccination schedules and nutrition for each stage of the baby's development.

[0681] A means of sending monitoring data to a server in real time

[0682] The monitoring data is sent to a server in real time. The server immediately processes the received data and responds immediately if an abnormality occurs. This real-time processing enables prompt and appropriate childcare support.

[0683] Adding specific examples

[0684] For example, when a user enters basic information about a newborn into a smartphone app, the system sends this information to the server and stores it in a database. When the device detects the baby's crying, the server analyzes the data and sends a notification to the user, asking them to check if the baby's temperature is normal.

[0685] Example prompts to input to the generative AI model

[0686] "Generate tips on how to deal with a crying baby at night."

[0687] "Detect baby cries and provide emergency response based on that."

[0688] "Please tell me in detail how to provide first aid if a newborn baby's temperature suddenly rises."

[0689] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0690] Step 1:

[0691] The user uses a smartphone application to enter basic information such as the newborn's name, date of birth, and gender. The information entered by the user is sent from the smartphone application to the server and stored in a database. At this stage, input: basic information (name, date of birth, gender), output: basic information stored in the database. Specifically, when the user enters the required information into the application form and presses the "Submit" button, the data is sent to the server.

[0692] Step 2:

[0693] The device uses a camera and microphone to monitor the newborn's movements and voice 24 hours a day. The collected data is sent to a server in real time. Input: Newborn's movements and voice data, Output: Monitoring data sent to the server. Specifically, the device's built-in camera and microphone continuously capture video and audio, and send this data to the server via the network.

[0694] Step 3:

[0695] The server analyzes the received monitoring data and models the newborn's daily rhythms and behavioral patterns. Based on the analysis results, it generates specific child-rearing advice. Input: Monitoring data, Output: Child-rearing advice. Specifically, a data analysis algorithm runs within the server, and if the baby is crying a lot at night, for example, it generates advice such as "play music at a steady rhythm."

[0696] Step 4:

[0697] The server notifies the user of the generated parenting advice via a smartphone application. Input: Parenting advice, Output: Parenting advice displayed on the smartphone. Specifically, the server sends a notification to the user's smartphone, and the advice is displayed in the app's notification center or pop-up.

[0698] Step 5:

[0699] The device monitors the newborn's abnormal movements and sounds, and if an abnormality is detected, it immediately notifies the server. The server analyzes the abnormal data and, if it determines that there is an emergency, automatically notifies the designated emergency contacts. Input: Abnormal movement and sound data, Output: Emergency notification. Specifically, when an abnormality is detected, the device sends data to the server, and the server notifies the emergency contacts by phone or SMS.

[0700] Step 6:

[0701] When the user reaches the next growth stage, the server sends the user a notification to migrate to a new device. The user accepts and configures the new device. When the device is connected, the server migrates all personal data to the new device. Input: Information about the new device, Output: Data migrated to the new device. Specifically, the user connects the new device to Wi-Fi and sends information to the server, and the server copies the original data to the new device.

[0702] Step 7:

[0703] The server provides parenting advice tailored to the newborn's developmental stage and emergency response measures. Input: Developmental stage information, Output: Advice and response measures according to the developmental stage. Specifically, the server compares the data with past data to determine the developmental stage, generates the necessary parenting advice and emergency response measures, and notifies the app.

[0704] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0705] The following system and its processing will be described as an embodiment of the present invention. This system provides optimized services by replacing devices according to the needs of a user as they grow from newborn, while inheriting personal data. Furthermore, it includes an emotion engine that recognizes the user's emotions and adjusts advice based on those emotions.

[0706] Overall system configuration

[0707] The system consists of the following main components:

[0708] 1. A way to enter basic information about newborns

[0709] 2. A means of collecting data by monitoring the movements and sounds of newborns

[0710] 3. A means of analyzing collected data and providing advice to users

[0711] 4. Means of emergency contact when an abnormality is detected

[0712] 5. A way to transfer data to the next device as users grow

[0713] 6. Emotion engine that recognizes user emotions

[0714] 7. Means for analyzing the emotional data recognized by the emotion engine and adjusting the advice

[0715] Each element is specifically implemented as follows:

[0716] A means of entering basic information about a newborn

[0717] For the initial setup, the user uses a smartphone app to enter basic information such as the newborn's name, date of birth, and gender. The device receives this information, sends it to a server, and stores it in a database. This information forms the basis for personalization in all subsequent processes.

[0718] A means of monitoring and collecting data on newborn movements and sounds

[0719] The device uses a camera and microphone to monitor the newborn's movements and sounds 24 / 7, including the baby's crying, sleep patterns, and body movements, and the collected data is sent to a server in real time.

[0720] A means of analyzing collected data and providing advice to users

[0721] The server analyzes the collected data and models the newborn's daily rhythm and characteristics. Based on the analysis results, it generates specific childcare advice for the user. For example, if a baby frequently cries at night, the server will provide the user with advice such as "play music at a steady rhythm." The device then notifies the user of this advice via a smartphone app.

[0722] A means of making emergency contact when an abnormality is detected

[0723] The device detects abnormal movements or sounds from the newborn. The server analyzes the abnormal data, determines whether it is an emergency, and automatically sends an emergency notification to designated contacts (e.g., emergency services, parents). The user receives the emergency notification via a smartphone app, allowing them to respond quickly.

[0724] A way to transfer data to the next device as users grow

[0725] When the user turns two years old, the server sends a notification to transition to a device suitable for the next stage of development. The user purchases a new device and sets it up. The device establishes the new device's Wi-Fi settings and connects to the server. The server transfers all personal data to the new device and continues to provide consistent support.

[0726] Emotion engine that recognizes user emotions

[0727] The device uses a camera and voice recognition technology to analyze the user's facial expressions and tone of voice, and an emotion engine to recognize the user's emotions, allowing it to more accurately understand the baby's needs and discomfort.

[0728] A means of analyzing the emotional data recognized by the emotion engine and adjusting the advice

[0729] The server analyzes the emotional data collected by the emotion engine to assess the user's current emotional state. For example, if the server determines that the user is under stress, it will provide special care advice. This advice is dynamically adjusted according to the user's emotional state, enabling more personalized care.

[0730] Processing explanation in natural language with concrete examples

[0731] For example, when a user enters basic information about a newborn into a smartphone app, the device sends this information to a server and stores it in a database. The device then uses a camera and microphone to monitor the baby's movements and sounds 24 / 7. The collected data is sent to the server in real time, which analyzes it. For example, if the server detects that the baby is crying frequently at night, it will notify the user through the smartphone app with advice to "play music at a regular rhythm." Furthermore, if the device detects abnormal movements or sounds from the baby, the server will determine this is an emergency and automatically contact emergency services. Finally, when the user turns two years old, the server will transfer the data to a new device, providing consistent support for childcare.

[0732] By introducing the emotion engine, it becomes possible to more accurately grasp the baby's emotional state and provide appropriate care. For example, if the server recognizes that the baby is feeling strong anxiety in a particular situation, it will provide special advice to the user to provide a sense of security. In this way, the emotion engine realizes optimal support according to the user's emotions.

[0733] The processing flow will be explained below.

[0734] Step 1:

[0735] The user opens the smartphone app and connects the new monitoring camera device to Wi-Fi.

[0736] Step 2:

[0737] The device checks the Internet connection and performs a connection test to the server.

[0738] Step 3:

[0739] The server verifies the connection and sends the settings screen to the user.

[0740] Step 4:

[0741] The user enters basic information about the newborn baby, such as their name, date of birth, and gender, on the app's settings screen.

[0742] Step 5:

[0743] The terminal receives the information entered by the user and transmits it to the server.

[0744] Step 6:

[0745] The server stores the received information in a database.

[0746] Step 7:

[0747] The device uses a camera and microphone to monitor the newborn's movements and sounds 24 hours a day.

[0748] Step 8:

[0749] The data collected by the device is sent to the server in real time.

[0750] Step 9:

[0751] The server receives the data and performs pre-processing (noise removal, time synchronization, etc.).

[0752] Step 10:

[0753] The server analyzes the preprocessed data and models the newborn's daily rhythms and characteristics.

[0754] Step 11:

[0755] The server generates specific child-rearing advice based on the analysis results.

[0756] Step 12:

[0757] The server notifies the user of the generated advice.

[0758] Step 13:

[0759] The device displays a notification to the user via a smartphone app, saying, "The baby has started crying. Please play music."

[0760] Step 14:

[0761] The user confirms the notification and starts playing music in the app.

[0762] Step 15:

[0763] The device will play music and continue to monitor your baby's condition.

[0764] Step 16:

[0765] The device detects abnormal movements or sounds from the baby.

[0766] Step 17:

[0767] Any abnormality information detected by the device is immediately sent to the server.

[0768] Step 18:

[0769] The server analyzes the abnormal data and determines whether it is an emergency.

[0770] Step 19:

[0771] If the server determines that an emergency exists, it will automatically send an emergency notification to the designated contacts.

[0772] Step 20:

[0773] The device sends an emergency notification to the user, displaying the message "Your baby is in danger. Call an ambulance."

[0774] Step 21:

[0775] Users can check emergency notifications and take appropriate action immediately.

[0776] Step 22:

[0777] The server sends a notification to the user to transition to a new device when the user turns two years old.

[0778] Step 23:

[0779] The device will display a message saying "Please move to the next stage device" and provide guidelines.

[0780] Step 24:

[0781] A user purchases a new device and sets it up for initial setup.

[0782] Step 25:

[0783] The device establishes a Wi-Fi connection for the new device and connects to the server.

[0784] Step 26:

[0785] The server will transfer all existing data to the new device.

[0786] Step 27:

[0787] The device receives the migrated data and starts new support tailored to the growing user base.

[0788] Step 28:

[0789] The server analyzes the monitoring data from the new device and continues to provide consistent parenting support.

[0790] Step 29:

[0791] The device uses a camera and microphone to collect the user's facial expressions and tone of voice.

[0792] Step 30:

[0793] The data collected by the device is sent to the server in real time.

[0794] Step 31:

[0795] The server uses an emotion engine to analyze the collected data and recognize the user's emotional state.

[0796] Step 32:

[0797] The server adjusts the parenting advice based on the emotional data.

[0798] Step 33:

[0799] The server notifies the user of the adjusted advice.

[0800] Step 34:

[0801] The device displays a message via a smartphone app saying, "Your baby seems anxious. Please hold him."

[0802] Step 35:

[0803] The user sees the notification and takes the appropriate action.

[0804] Example 2

[0805] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0806] Modern childcare demands personalized services that meet the needs of children from newborn to adulthood. However, conventional systems have struggled to provide services while consistently transferring data and replacing devices appropriately as users grow. Recognizing users' emotions and providing appropriate advice is also a challenge. Furthermore, systems lacked the ability to quickly and automatically contact emergency personnel when an abnormality was detected.

[0807] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0808] In this invention, the server includes means for inputting basic information about the user, means for collecting data by monitoring the user's movements and voice, means for analyzing the collected data and providing advice to the user, means for making emergency contact when an abnormality is detected, means for transferring data to a subsequent device in accordance with the user's growth, an emotion engine for recognizing the user's emotions, and means for analyzing the emotion data recognized by the emotion engine and adjusting advice. This enables device replacement and data transfer in accordance with the user's growth, provision of personalized services based on emotions, and rapid emergency response.

[0809] The term "user" refers to a person who uses the system, and in the present invention refers to all users including newborns and their growing children.

[0810] The term "device" refers to all hardware devices used in the system of the present invention, including monitoring devices, recording devices, communication devices, and the like.

[0811] "Basic Information" refers to the default information about a User, including personally identifiable information such as name, date of birth, and gender.

[0812] "Means for monitoring movements and sounds" refers to the function of recording and collecting user actions and sounds in real time using input devices such as cameras and microphones.

[0813] "Data collection means" means any process or device that temporarily or permanently stores information such as a user's movements or voice.

[0814] "Means for analyzing data" refers to functions, including software and algorithms, that analyze collected data and identify specific patterns or trends.

[0815] "Means for providing advice" means a system function for making suggestions to users regarding childcare and health management based on the analysis results.

[0816] "Means for making emergency contact" refers to the function of promptly sending warnings or notifications to the user or designated third parties via communication means when an abnormality is detected.

[0817] "Means for transferring data" refers to the ability to transfer data from an old device to a new device as the user grows.

[0818] "Emotion-aware emotion engine" means specialized algorithms and software that analyze a user's facial expressions and tone of voice to recognize their emotional state.

[0819] "Means for analyzing emotional data and adjusting advice" refers to the function of appropriately adjusting the content of advice based on emotional data recognized by the emotion engine, thereby providing a more personalized service.

[0820] The system of the present invention aims to provide personalized services through device replacement, data transfer, and emotion recognition in accordance with the user's growth. This system is composed of multiple hardware and software components, the role of which is described in detail below.

[0821] Overall system configuration

[0822] The system consists of the following main components:

[0823] 1. A way to enter basic user information

[0824] 2. Collecting data by monitoring your movements and voice

[0825] 3. A means of analyzing collected data and providing advice to users

[0826] 4. Means of emergency contact when an abnormality is detected

[0827] 5. A way to transfer data to the next device as the user grows

[0828] 6. Emotion engine that recognizes user emotions

[0829] 7. Means for analyzing the emotional data recognized by the emotion engine and adjusting the advice

[0830] A means of entering basic user information

[0831] For initial setup, the user uses a smartphone application to enter basic information such as the user's name, date of birth, gender, etc. The device receives this information, sends it to the server, and stores it in a database. This information forms the basis for personalization in all subsequent processes.

[0832] A means of collecting data by monitoring user movements and voices

[0833] The device uses a camera and microphone to monitor the user's movements and voice 24 / 7, including movement patterns, tone of voice, facial expressions, etc. The collected data is sent to a server in real time.

[0834] A means of analyzing collected data and providing advice to users

[0835] The server analyzes the collected data and models the user's lifestyle and characteristics. Based on the analysis results, it generates specific advice for the user. For example, if the server recognizes that the user is feeling stressed, it will provide the advice "listen to music to relax." The device then notifies the user of this advice via a smartphone application.

[0836] A means of making emergency contact when an abnormality is detected

[0837] The device detects the user's abnormal movements or sounds. The server analyzes the abnormal data, determines that it is an emergency, and automatically sends an emergency notification to designated contacts (e.g., emergency contacts). The user receives the emergency notification through a smartphone application and can respond quickly.

[0838] A way to transfer data to the next device as the user grows

[0839] As a user grows, the server sends a migration notification to a device suitable for the next stage of growth. The user purchases a new device and performs initial setup. The device establishes the network settings for the new device and connects to the server. The server migrates all data to the new device and continues to provide consistent support.

[0840] Emotion engine that recognizes user emotions

[0841] The device uses a camera and voice recognition technology to analyze the user's facial expressions and tone of voice, and an emotion engine to recognize the user's emotions, allowing it to more accurately understand the user's needs and complaints.

[0842] A means of analyzing the emotional data recognized by the emotion engine and adjusting the advice

[0843] The server analyzes the emotion data collected by the emotion engine to assess the user's current emotional state. For example, if the server determines that the user is under stress, it provides special care advice. This advice is dynamically adjusted according to the user's emotional state, enabling more personalized care.

[0844] Processing explanation in natural language with concrete examples

[0845] For example, when a user enters basic information about a newborn into a smartphone app, the device sends this information to a server and stores it in a database. The device then uses a camera and microphone to monitor the baby's movements and sounds 24 / 7. The collected data is sent to the server in real time, which analyzes it. For example, if the server detects that the baby is crying frequently at night, it will notify the user through the smartphone app with advice to "play music at a regular rhythm." Furthermore, if the device detects abnormal movements or sounds from the baby, the server will determine this is an emergency and automatically contact emergency services. Finally, when the user turns two years old, the server will transfer the data to a new device, providing consistent childcare support.

[0846] Example prompts for generative AI models

[0847] "When a user uses a smartphone app to enter basic information about a newborn baby, please explain the specific processing steps of how that information is sent to the server and stored in the database."

[0848] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0849] Step 1:

[0850] The user launches a smartphone application and enters basic information about the newborn baby. The entered basic information includes the baby's name, date of birth, and gender. This information is collected within the application and sent to the device. The device converts this information into JSON format and sends it to the server using the HTTPS protocol. The server saves the received data in a database and returns a save completion response to the device.

[0851] Specific operation:

[0852] 1. The user opens the app's input form and enters the newborn's information.

[0853] 2. The device serializes the user input data into JSON.

[0854] 3. The device sends data to the server via HTTPS.

[0855] 4. The server validates the incoming data and saves it as a new record in the database.

[0856] 5. The server returns a save completion response to the terminal, and the terminal notifies the user.

[0857] Step 2:

[0858] The device monitors the user's movements and voice 24 / 7 using a camera and microphone. This monitoring captures the user's movement and voice patterns. This data is stored in a buffer at regular intervals and then securely transmitted to a server using a VPN.

[0859] Specific operation:

[0860] 1. The device begins capturing real-time data using the camera and microphone.

[0861] 2. Movement and audio data are temporarily stored in a buffer.

[0862] 3. At regular intervals, the contents of the buffer are sent to the server via VPN.

[0863] Step 3:

[0864] The server analyzes the received data and models the user's lifestyle and characteristics. The received data is processed by an analysis module to extract specific patterns and trends. This generates a user behavior model that is stored in a database.

[0865] Specific operation:

[0866] 1. The server passes the received data to a dedicated module that analyzes it.

[0867] 2. The analytics module runs algorithms that identify behavioral patterns and trends.

[0868] 3. Identified patterns and trends are modeled and stored in a database.

[0869] Step 4:

[0870] The server generates advice for the user based on the analysis results. The generated advice is notified to the user via a smartphone application. For example, if the server recognizes that the user is feeling stressed, it will provide the advice "listen to music to relax."

[0871] Specific operation:

[0872] 1. The server selects an advice template based on the analysis results.

[0873] 2. A specific message is generated based on the selected template.

[0874] 3. The generated advice is sent to the device, which then notifies the user via an app notification.

[0875] Step 5:

[0876] The device runs an algorithm to detect abnormal user movements or sounds. If an abnormality is detected, it sends an alert to the server. The server analyzes the alert data and, if an abnormality is detected, sends a notification to designated emergency contacts. The user receives the emergency notification through a smartphone application.

[0877] Specific operation:

[0878] 1. The device runs an anomaly detection algorithm that monitors real-time data.

[0879] 2. If an abnormality is detected, an alert is sent to the server immediately.

[0880] 3. The server analyzes the alert and, if it determines that there is an abnormality, sends a notification to the registered emergency contact.

[0881] 4. Users receive emergency notifications through the app and respond quickly.

[0882] Step 6:

[0883] The server sends migration notifications to new devices as users grow. The user purchases a new device and performs initial setup. The device establishes network settings for the new device and connects to the server. The server migrates all data to the new device and continues to provide consistent support.

[0884] Specific operation:

[0885] 1. The server monitors the user's growth data and generates migration notifications at appropriate times.

[0886] 2. The user purchases a new device and goes through the initial setup procedure.

[0887] 3. The device completes the network configuration of the new device and connects to the server.

[0888] 4. The server transfers the data from the old device to the new device.

[0889] Step 7:

[0890] The device uses a camera and voice recognition technology to analyze the user's facial expressions and tone of voice, and recognizes the user's emotions using an emotion engine. This data is sent to a server, which then analyzes it using the emotion engine. Based on the analysis results, tailored advice is provided to the user.

[0891] Specific operation:

[0892] 1. The device uses a camera and microphone to perform facial recognition and voice analysis.

[0893] 2. The analyzed data is sent to the server in real time.

[0894] 3. The server passes the data to the emotion engine to evaluate the user's emotional state.

[0895] 4. Based on the evaluation results, generate and notify tailored advice to the user.

[0896] (Application example 2)

[0897] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0898] While modern childcare demands personalized support tailored to each newborn's developmental stage, manual information management and decision-making are required, increasing the burden of childcare. It is also difficult to accurately grasp a newborn's emotional state and provide appropriate care based on that. Furthermore, childcare products and services are typically offered in brick-and-mortar stores, lacking personalization tailored to individual needs. This often results in inadequate childcare support.

[0899] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for inputting basic information about the newborn, a means for monitoring the newborn's movements and voice to collect data, a means for analyzing the collected data and providing advice to the user, a means for making an emergency call when an abnormality is detected, a means for recognizing the user's emotions and adjusting advice based on the emotion data, a means for transferring data to the next device as the user grows, and a means for proposing personalized products and services in physical stores and providing special care counseling. This enables seamless childcare support according to the newborn's growth stage, provision of appropriate care based on the newborn's emotional state, consistent data management, and provision of personalized services in physical stores according to individual needs.

[0900] "Means for inputting basic information about a newborn" is a function that allows a user to input basic information about a newborn, such as the name, date of birth, and gender, and send it to the server.

[0901] "Means for monitoring the movements and sounds of newborns and collecting data" refers to a function that uses cameras and microphones to monitor the movements and sounds of newborns 24 hours a day and collect data.

[0902] "Means for analyzing collected data and providing advice to users" refers to a function in which the server analyzes collected data, models the daily rhythms and characteristics of the newborn, and provides appropriate child-rearing advice to users.

[0903] "Means for making emergency contact when an abnormality is detected" is a function that allows the system to detect abnormal movements or sounds from the newborn and automatically notify emergency contacts.

[0904] "Means for recognizing the user's emotions and adjusting advice based on emotional data" refers to a function that uses an emotion engine to analyze the user's facial expressions and tone of voice and adjust advice to provide appropriate care.

[0905] "A way to transfer data to the next device as the user grows" is a feature that allows existing data to be transferred to a new device as the newborn grows, providing consistent parenting support.

[0906] "Means of proposing personalized products and services in physical stores and providing special care counseling" refers to a function that personalizes the proposal of childcare products and services in physical stores and provides care counseling according to individual needs.

[0907] The following system and its processing will be described as an embodiment of the present invention. This system provides optimized services by replacing devices according to the needs of a user as they grow from newborn, while inheriting personal data. Furthermore, it includes an emotion engine that recognizes the user's emotions and adjusts advice based on those emotions.

[0908] Overall system configuration

[0909] The system consists of the following main components:

[0910] 1. A way to enter basic information about newborns

[0911] 2. A means of collecting data by monitoring the movements and sounds of newborns

[0912] 3. A means of analyzing collected data and providing advice to users

[0913] 4. Means of emergency contact when an abnormality is detected

[0914] 5. A way to recognize user emotions and tailor recommendations based on emotional data

[0915] 6. A way to transfer data to the next device as users grow

[0916] 7. A way to offer personalized products and services in physical stores and provide special care counseling

[0917] A means of entering basic information about a newborn

[0918] For the initial setup, the user uses a smartphone app to enter basic information about the newborn, such as their name, date of birth, and gender. The device receives this information, sends it to a server, and stores it in a database. This information forms the basis for personalization in all subsequent processes.

[0919] A means of monitoring and collecting data on newborn movements and sounds

[0920] The device uses a camera and microphone to monitor the newborn's movements and sounds 24 / 7, including the baby's crying, sleep patterns, and body movements, and the collected data is sent to a server in real time.

[0921] A means of analyzing collected data and providing advice to users

[0922] The server analyzes the collected data and models the newborn's daily rhythm and characteristics. Based on the analysis results, it generates specific childcare advice for the user. For example, if a baby frequently cries at night, the server will provide the user with advice such as "play music at a steady rhythm." The device then notifies the user of this advice via a smartphone app.

[0923] A means of making emergency contact when an abnormality is detected

[0924] The device detects abnormal movements or sounds from the newborn. The server analyzes the abnormal data, determines whether it is an emergency, and automatically sends an emergency notification to designated contacts (e.g., ambulance, parents). The user receives the emergency notification through a smartphone app and can respond quickly.

[0925] A means of recognizing user emotions and tailoring advice based on emotional data

[0926] The device uses a camera and voice recognition technology to analyze the user's facial expressions and tone of voice, and recognizes the user's emotions using an emotion engine. This allows for more accurate understanding of the baby's needs and ailments. The server analyzes the emotion data collected by the emotion engine and evaluates the user's current emotional state. For example, if the server determines that the user is under stress, it will provide special care advice. This advice is dynamically adjusted according to the user's emotional state, enabling more personalized care.

[0927] A way to transfer data to the next device as users grow

[0928] When the user turns two years old, the server sends a notification to transition to a device suitable for the next stage of development. The user purchases a new device and sets it up. The device establishes the new device's Wi-Fi settings and connects to the server. The server transfers all personal data to the new device and continues to provide consistent support.

[0929] A means to offer personalized products and services in physical stores and provide special care counseling

[0930] There is a smartphone app that provides childcare products and services in brick-and-mortar stores, and the server proposes personalized products and services based on basic information about the newborn, their daily movements, and emotional data. The app also allows users to make reservations for care counseling sessions in brick-and-mortar stores and receive consultations in real time.

[0931] Specific examples

[0932] For example, when a user enters basic information about a newborn baby into a smartphone app, the device sends this information to a server and stores it in a database. The device then uses a camera and microphone to monitor the baby's movements and sounds 24 hours a day. The collected data is sent in real time to the server, which analyzes it. For example, if the server detects that the baby is crying frequently at night, it will notify the user through the smartphone app with advice to "play music at a regular rhythm."

[0933] By introducing the emotion engine, it becomes possible to more accurately grasp the baby's emotional state and provide appropriate care. For example, if the server recognizes that the baby is feeling strong anxiety in a particular situation, it will provide special advice to the user to provide a sense of security. In this way, the emotion engine realizes optimal support according to the user's emotions.

[0934] Example prompts for generative AI models

[0935] Generate the best advice for your crying baby based on the following data:

[0936] Basic information: Name "Newborn A", Date of birth "2022-01-01", Gender "Male"

[0937] Movement and sound data: "Frequent crying at night"

[0938] Emotion data: "crying face" and "anxious voice"

[0939] Output formats:

[0940] Advice: New Instructions

[0941] Additional Care Suggestions: Special Care Suggestions

[0942] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0943] Step 1:

[0944] The user enters basic information about the newborn into a smartphone app.

[0945] How it works: The user uses the app's input form to enter the newborn's name, date of birth, and gender, and the information is sent by the device to the server and stored in a database.

[0946] Input: Newborn's name, date of birth, sex

[0947] Output: Basic information of the newborn stored in the database

[0948] Step 2:

[0949] The device uses a camera and microphone to monitor the newborn's movements and sounds and collect data.

[0950] How it works: The device periodically activates the camera and microphone to monitor the newborn's movements and cries, and the collected data is sent to the server in real time.

[0951] Input: Video and audio data from the camera and microphone

[0952] Output: Monitoring data of the newborn's movements and voices sent to a server

[0953] Step 3:

[0954] The server analyzes the collected data and models the newborn's daily rhythms and characteristics.

[0955] How it works: The server analyzes the received data using machine learning algorithms to identify the time of day when the newborn is crying and their movement patterns.

[0956] Input: Neonatal movement and voice monitoring data

[0957] Output: Data modeling the daily rhythms and characteristics of newborns

[0958] Step 4:

[0959] The server generates parenting advice based on the analysis results and notifies the user via the device.

[0960] Specific operation: Based on the analysis data, the server creates parenting advice, such as "play music at a steady rhythm," and notifies the user via a smartphone app.

[0961] Input: Data modeling the daily rhythms and characteristics of newborns

[0962] Output: Parenting advice sent to a smartphone app

[0963] Step 5:

[0964] If the device detects any abnormal movements or sounds from the newborn, the server will automatically send an emergency notification.

[0965] Specific operation: When the device detects an abnormality, it sends the data to the server, which determines it is an emergency and automatically sends a notification to pre-defined emergency contacts.

[0966] Input: Unusual movement and audio data

[0967] Output:Notify emergency contacts

[0968] Step 6:

[0969] The device uses a camera and voice recognition technology to collect the user's emotional data, which is then analyzed by the server to tailor the advice.

[0970] How it works: The device uses a camera to capture the user's facial expressions and a microphone to analyze the tone of voice. The collected emotional data is sent to the server, which then adjusts the advice based on the user's emotional state.

[0971] Input: Emotion data from camera and microphone

[0972] Output: Advice based on emotional state

[0973] Step 7:

[0974] As the user grows, the server sends a notification for the next device migration and transfers the data to the new device.

[0975] What it does: When a user purchases and sets up a new device, the device establishes the device's Wi-Fi settings and connects to the server, which then transfers all personal data to the new device.

[0976] Input: New device setup information

[0977] Output: Personal data transferred to new device

[0978] Step 8:

[0979] Servers will suggest personalized products and services in physical stores and provide special care counseling.

[0980] How it works: The server recommends optimal products and services at physical stores based on the newborn's basic information, daily movements, and emotional data. The app also allows users to make appointments for special care counseling.

[0981] Input: Basic information of newborn baby, movement and voice data, emotion data

[0982] Output: Personalized recommendations and care counseling in physical stores

[0983] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0984] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0985] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0986] [Third embodiment]

[0987] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0988] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0989] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0990] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0991] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0992] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0993] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0994] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0995] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0996] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0997] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0998] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0999] The following system and its processing will be described as an embodiment of the present invention. This system provides optimized services by replacing devices according to the needs of users growing from newborns, while inheriting personal data.

[1000] Overall system configuration

[1001] The system consists of the following main components:

[1002] 1. A way to enter basic information about newborns

[1003] 2. A means of collecting data by monitoring the movements and sounds of newborns

[1004] 3. A means of analyzing collected data and providing advice to users

[1005] 4. Means of emergency contact when an abnormality is detected

[1006] 5. A way to transfer data to the next device as users grow

[1007] Each element is specifically implemented as follows:

[1008] A means of entering basic information about a newborn

[1009] For the initial setup, the user uses a smartphone app to enter basic information such as the newborn's name, date of birth, and gender. The device receives this information, sends it to a server, and stores it in a database. This information forms the basis for personalization in all subsequent processes.

[1010] A means of monitoring and collecting data on newborn movements and sounds

[1011] The device uses a camera and microphone to monitor the newborn's movements and sounds 24 / 7, including the baby's crying, sleep patterns, and body movements, and the collected data is sent to a server in real time.

[1012] A means of analyzing collected data and providing advice to users

[1013] The server analyzes the collected data and models the newborn's daily rhythm and characteristics. Based on the analysis results, it generates specific childcare advice for the user. For example, if a baby frequently cries at night, the server will provide the user with advice such as "play music at a steady rhythm." The device then notifies the user of this advice via a smartphone app.

[1014] A means of making emergency contact when an abnormality is detected

[1015] The device detects abnormal movements or sounds from the newborn. The server analyzes the abnormal data, determines whether it is an emergency, and automatically sends an emergency notification to designated contacts (e.g., emergency services, parents). The user receives the emergency notification via a smartphone app, allowing them to respond quickly.

[1016] A way to transfer data to the next device as users grow

[1017] When the user turns two years old, the server sends a notification to transition to a device suitable for the next stage of development. The user purchases a new device and sets it up. The device establishes the new device's Wi-Fi settings and connects to the server. The server transfers all personal data to the new device and continues to provide consistent support.

[1018] Processing explanation in natural language with concrete examples

[1019] For example, when a user enters basic information about a newborn into a smartphone app, the device sends this information to a server and stores it in a database. The device then uses a camera and microphone to monitor the baby's movements and sounds 24 / 7. The collected data is sent to the server in real time, which analyzes it. For example, if the server detects that the baby is crying frequently at night, it will notify the user through the smartphone app with advice to "play music at a regular rhythm." Furthermore, if the device detects abnormal movements or sounds from the baby, the server will determine this is an emergency and automatically contact emergency services. Finally, when the user turns two years old, the server will transfer the data to a new device, providing consistent support for childcare.

[1020] This allows users to receive consistent support as their child grows from birth, reducing the burden of childcare.

[1021] The processing flow will be explained below.

[1022] Step 1:

[1023] The user opens the smartphone app and connects the new monitoring camera device to Wi-Fi.

[1024] Step 2:

[1025] The device checks the Internet connection and performs a connection test to the server.

[1026] Step 3:

[1027] The server verifies the connection and sends the settings screen to the user.

[1028] Step 4:

[1029] The user enters basic information about the newborn baby, such as their name, date of birth, and gender, on the app's settings screen.

[1030] Step 5:

[1031] The terminal receives the information entered by the user and transmits it to the server.

[1032] Step 6:

[1033] The server stores the received information in a database.

[1034] Step 7:

[1035] The device uses a camera and microphone to monitor the newborn's movements and sounds 24 hours a day.

[1036] Step 8:

[1037] The data collected by the device is sent to the server in real time.

[1038] Step 9:

[1039] The server receives the data and performs pre-processing (noise removal, time synchronization, etc.).

[1040] Step 10:

[1041] The server analyzes the preprocessed data and models the newborn's daily rhythms and characteristics.

[1042] Step 11:

[1043] The server generates specific child-rearing advice based on the analysis results.

[1044] Step 12:

[1045] The server notifies the user of the generated advice.

[1046] Step 13:

[1047] The device displays a notification to the user via a smartphone app, saying, "The baby has started crying. Please play music."

[1048] Step 14:

[1049] The user confirms the notification and starts playing music in the app.

[1050] Step 15:

[1051] The device will play music and continue to monitor your baby's condition.

[1052] Step 16:

[1053] The device detects abnormal movements or sounds from the baby.

[1054] Step 17:

[1055] Any abnormality information detected by the device is immediately sent to the server.

[1056] Step 18:

[1057] The server analyzes the abnormal data and determines whether it is an emergency.

[1058] Step 19:

[1059] If the server determines that an emergency exists, it will automatically send an emergency notification to the designated contacts.

[1060] Step 20:

[1061] The device sends an emergency notification to the user, displaying the message "Your baby is in danger. Call an ambulance."

[1062] Step 21:

[1063] Users can check emergency notifications and take appropriate action immediately.

[1064] Step 22:

[1065] The server sends a notification to the user to transition to a new device when the user turns two years old.

[1066] Step 23:

[1067] The device will display a message saying "Please move to the next stage device" and provide guidelines.

[1068] Step 24:

[1069] A user purchases a new device and sets it up for initial setup.

[1070] Step 25:

[1071] The device establishes a Wi-Fi connection for the new device and connects to the server.

[1072] Step 26:

[1073] The server will transfer all existing data to the new device.

[1074] Step 27:

[1075] The device receives the migrated data and starts new support tailored to the growing user base.

[1076] Step 28:

[1077] The server analyzes the monitoring data from the new device and continues to provide consistent parenting support.

[1078] Example 1

[1079] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1080] Conventional childcare support systems have the problem of making it difficult to properly replace devices and transfer data as the baby grows from birth. Furthermore, data collection, analysis, and advice provision of newborn movements and voices are often inconsistent, making it difficult to respond quickly in emergencies. This creates the problem of parents being unable to receive consistent childcare support and increasing the burden of childcare on parents.

[1081] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1082] In this invention, the server includes means for inputting basic information, means for monitoring movements and sounds and collecting data, means for analyzing the collected data and providing advice, means for making emergency contact when an abnormality is detected, means for transferring data to the next device as the user grows, means for analyzing the collected data using a machine learning model and modeling daily rhythms and characteristics, and means for automatically making emergency contact and notifying designated contacts. This enables consistent childcare support according to the user's stage of growth and reduces the burden on parents.

[1083] "Basic information" refers to information about the user that is necessary for initial setup, such as name, date of birth, and gender.

[1084] "Movement and sound" refers to data on the newborn's body movements, cries, and other vocalizations.

[1085] The "means of collecting data" refers to the method of using a camera and microphone to monitor the newborn's movements and sounds and collecting this data on a terminal.

[1086] "Means for analyzing collected data" refers to methods for analyzing the daily rhythms and characteristics of newborns using collected data, and in particular, machine learning models are often used to perform highly accurate analysis.

[1087] The "means for providing advice" is a method for generating and notifying specific child-rearing advice to the user based on the analysis results.

[1088] "Means for detecting abnormalities" refers to a method of constantly monitoring the movements and sounds of the newborn and detecting any abnormal patterns.

[1089] "Means for making emergency contact" refers to a method for automatically sending a notification to designated contacts when an abnormality is detected.

[1090] "Means for transferring data" refers to a method for transferring data from a newborn to a new device suitable for the next stage of development.

[1091] "Machine learning model" refers to the algorithms and techniques used for analysis and modeling using collected data.

[1092] "Designated Contact" means the contact information for a parent, emergency services, or other person who should be contacted in an emergency.

[1093] Overall system configuration

[1094] This system allows users to exchange terminals as they grow, and provides consistent services while transferring data. The main elements of the system and their processing are explained below.

[1095] Enter basic information

[1096] For the initial setup, the user uses a smartphone application to enter basic information about the newborn, such as their name, date of birth, and gender. This information is then encrypted and sent from the device to a server, which stores it in a database, allowing for any necessary personalization during subsequent processes.

[1097] Data collection

[1098] The device uses a camera and microphone to monitor the newborn's movements and voice in real time. Specifically, the camera tracks the baby's position and movements, and the microphone detects crying and other sounds. This data is periodically sent to a server for real-time data collection.

[1099] Data analysis

[1100] The server analyzes the collected data. Generative AI models are used to achieve highly accurate data analysis. This analysis allows the newborn's daily rhythms and characteristics to be modeled. For example, the server analyzes the baby's sleep patterns and crying frequency to identify outliers and general trends.

[1101] Providing advice

[1102] Based on the analysis results, the server generates specific childcare advice. High-precision advice is generated using a generative AI model. For example, if a baby frequently cries at night, the server will advise the user to "play music at a steady rhythm." The device then notifies the user of this advice via a smartphone app.

[1103] Anomaly detection and emergency contact

[1104] The device monitors the newborn's movements and sounds in real time. If an abnormality is detected, the device sends the information to a server. The server analyzes the received data and determines whether it is an emergency. In the event of an emergency, an emergency notification is automatically sent to designated contacts (e.g., parents, emergency services). Users can also receive emergency notifications through a smartphone app, enabling a prompt response.

[1105] Data transfer

[1106] As the user grows, for example, when they reach the age of two, the server sends them a notification to transition to a device suitable for their new stage of development. The user purchases a new device and performs initial setup, such as Wi-Fi settings. Once the device has completed the new device setup, the server transfers all personal data to the new device. This ensures consistent support for the new device.

[1107] Examples and prompts

[1108] For example, when a user enters basic information about a newborn baby into a smartphone app, the device sends it to a server and stores it in a database. The device uses a camera and microphone to monitor the baby's movements and sounds, sending the data to the server in real time. The server analyzes the data and generates advice such as "playing music at a steady rhythm" if the baby is crying frequently at night. In an emergency, emergency services will be automatically contacted. When the user reaches a new developmental stage, the data is transferred to a new device.

[1109] Specific prompt examples:

[1110] "How to build a system that analyzes a baby's sleep patterns and generates and notifies appropriate childcare advice"

[1111] As described above, this system provides users with consistent childcare support and provides concrete measures to reduce the burden of childcare.

[1112] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1113] Step 1: Enter basic information

[1114] The user opens the application on their smartphone and enters basic information about the newborn, such as the newborn's name, date of birth, and gender. The device encrypts this information and sends it to the server, which then stores the received information in a database. The input is the newborn's basic information, such as the newborn's name, date of birth, and gender, entered by the user, and the output is that this information is accurately stored in the database.

[1115] Step 2: Collect data

[1116] The device uses a camera and microphone to monitor the newborn's movements and voice 24 hours a day. The camera captures the baby's position and movements, while the microphone collects crying and other sounds. This data is sent from the device to a server in real time. The input is the newborn's real-time movements and voice data, and the output is sent appropriately to the server.

[1117] Step 3: Analyze the data

[1118] The server analyzes the collected data. It uses a generative AI model to perform highly accurate data analysis and model the newborn's daily rhythms and characteristics. The analyzed data includes the baby's sleep patterns and crying frequency. The server uses a machine learning model to extract outliers and general trends and outputs them as the analysis results. The input is movement and audio data transmitted in real time, and the output is the modeled analysis results.

[1119] Step 4: Providing advice

[1120] The server generates specific childcare advice based on the analysis results. The advice is created using a generative AI model and notified to the user via the device. For example, if a baby frequently cries at night, the server will generate advice such as "play music at a steady rhythm." The input is the result of data analysis, and the output is a notification of specific childcare advice.

[1121] Step 5: Anomaly detection and emergency notification

[1122] The device monitors the newborn's abnormal movements and sounds in real time. If any suspicious movements are detected, the device sends the information to a server. The server analyzes the abnormal data and determines whether it is an emergency. If an emergency is determined, an emergency notification is automatically sent to designated contacts. The user can also receive the emergency notification through a smartphone application. The input is real-time data for detecting an abnormality, and the output is a notification to contact the emergency services.

[1123] Step 6: Transfer data

[1124] As the user grows, for example, when they reach the age of two, the server sends them a notification to migrate to a device suitable for their new stage of development. The user purchases a new device and performs initial setup such as Wi-Fi settings. Once the device completes the new device setup, the server migrates all personal data to the new device. This provides consistent support on the new device. The input is the migration instruction for the new device, and the output is the migrated data.

[1125] (Application example 1)

[1126] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1127] Conventional newborn monitoring systems struggle to provide appropriate devices and services for newborns as they grow. They also lack sufficient emergency response and childcare advice tailored to the newborn's development. This results in users having to purchase individual devices or use different systems, increasing the burden of childcare. Furthermore, while rapid and appropriate responses are required when an abnormality is detected, such systems are limited. An effective system that solves these problems is needed.

[1128] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1129] In this invention, the server includes means for inputting basic information about the newborn, means for monitoring the newborn's movements and voices and collecting data, means for analyzing the collected data and providing advice to the user, means for making emergency contact when an abnormality is detected, means for transferring data to the next device as the user grows, means for providing childcare advice and emergency response measures according to the newborn's stage of growth, and means for transmitting monitored data to the server in real time, thereby enabling consistent childcare support according to the newborn's stage of growth and rapid response to abnormalities.

[1130] "Replacing devices as users grow" means replacing appropriate hardware or software devices with new ones to provide the features and services required by users as they grow.

[1131] "Data transfer" refers to the consistent transfer of all personal data from an old device to a new device, ensuring that users continue to receive seamless services.

[1132] "Means for inputting basic information about a newborn" refers to a means for using a user interface such as a smartphone or computer to input initial information such as the newborn's name, date of birth, and gender, and registering it in the system.

[1133] "Means for monitoring the movements and sounds of newborns and collecting data" refers to means for using sensors such as cameras and microphones to monitor the movements and sounds of newborns in real time and collect this data.

[1134] The "means for analyzing collected data and providing advice to users" refers to means that has the function of analyzing data sent to the server, generating specific advice regarding child-rearing, and providing it to users.

[1135] "Means for making emergency contact when an abnormality is detected" refers to a means for automatically sending a notification to a designated emergency contact if an abnormality is detected in the newborn's movements or voice.

[1136] "Means for transferring data to the next device as the user grows" refers to a means for transferring all personal data to an appropriate new device as the user grows, thereby enabling uninterrupted service provision.

[1137] "Means for providing childcare advice and emergency response measures according to the user's stage of development" refers to means that have the function of automatically generating and providing appropriate childcare advice and emergency response measures according to the user's age and stage of development.

[1138] The "means for transmitting monitoring data to a server in real time" refers to a means for transmitting monitoring data of the newborn's movements and voice to a server in real time via the Internet, enabling immediate processing and analysis.

[1139] The following system and its processing will be described as an embodiment of the present invention. This system provides optimal services by replacing devices as users grow and transferring data.

[1140] Overall system configuration

[1141] The system consists of the following main components:

[1142] 1. A way to enter basic information about newborns

[1143] 2. A means of collecting data by monitoring the movements and sounds of newborns

[1144] 3. A means of analyzing collected data and providing advice to users

[1145] 4. Means of emergency contact when an abnormality is detected

[1146] 5. A way to transfer data to the next device as users grow

[1147] 6. A means of providing stage-appropriate parenting advice and emergency response plans

[1148] 7. A means of sending monitoring data to the server in real time

[1149] A means of entering basic information about a newborn

[1150] For the initial setup, the user uses a smartphone application to enter basic information about the newborn, such as their name, date of birth, and gender. The device receives this information, sends it to a server, and stores it in a database. This information forms the basis for personalization in all subsequent processes.

[1151] A means of monitoring and collecting data on newborn movements and sounds

[1152] The device uses a camera and microphone to monitor the newborn's movements and sounds 24 / 7, including the baby's crying, sleep patterns, and body movements, and the collected data is sent to a server in real time.

[1153] A means of analyzing collected data and providing advice to users

[1154] The server analyzes the collected data and models the newborn's daily rhythm and characteristics. Based on the analysis results, it generates specific childcare advice for the user. For example, if a baby frequently cries at night, the server will provide the user with advice such as "play music at a steady rhythm." The device then notifies the user of this advice via a smartphone app.

[1155] A means of making emergency contact when an abnormality is detected

[1156] The device detects any abnormal movements or sounds from the newborn. The server analyzes the abnormal data, determines whether an emergency has occurred, and automatically sends an emergency notification to designated contacts. The user receives the emergency notification via a smartphone app, allowing them to respond quickly.

[1157] A way to transfer data to the next device as users grow

[1158] When a user reaches the next growth stage, the server sends a notification to migrate to a new device. The user sets up the next device, and the device establishes the new device's Wi-Fi settings and connects to the server. The server then migrates all personal data to the new device, providing consistent support.

[1159] A means of providing stage-specific parenting advice and emergency response plans

[1160] The server generates childcare advice and emergency response measures that are tailored to the newborn's development. For example, if it detects the baby's crying, it will send an alarm to the user, telling them to "check if the baby's temperature is normal." It also provides advice on vaccination schedules and nutrition for each stage of the baby's development.

[1161] A means of sending monitoring data to a server in real time

[1162] The monitoring data is sent to a server in real time. The server immediately processes the received data and responds immediately if an abnormality occurs. This real-time processing enables prompt and appropriate childcare support.

[1163] Adding specific examples

[1164] For example, when a user enters basic information about a newborn into a smartphone app, the system sends this information to the server and stores it in a database. When the device detects the baby's crying, the server analyzes the data and sends a notification to the user, asking them to check if the baby's temperature is normal.

[1165] Example prompts to input to the generative AI model

[1166] "Generate tips on how to deal with a crying baby at night."

[1167] "Detect baby cries and provide emergency response based on that."

[1168] "Please tell me in detail how to provide first aid if a newborn baby's temperature suddenly rises."

[1169] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1170] Step 1:

[1171] The user uses a smartphone application to enter basic information such as the newborn's name, date of birth, and gender. The information entered by the user is sent from the smartphone application to the server and stored in a database. At this stage, input: basic information (name, date of birth, gender), output: basic information stored in the database. Specifically, when the user enters the required information into the application form and presses the "Submit" button, the data is sent to the server.

[1172] Step 2:

[1173] The device uses a camera and microphone to monitor the newborn's movements and voice 24 hours a day. The collected data is sent to a server in real time. Input: Newborn's movements and voice data, Output: Monitoring data sent to the server. Specifically, the device's built-in camera and microphone continuously capture video and audio, and send this data to the server via the network.

[1174] Step 3:

[1175] The server analyzes the received monitoring data and models the newborn's daily rhythms and behavioral patterns. Based on the analysis results, it generates specific child-rearing advice. Input: Monitoring data, Output: Child-rearing advice. Specifically, a data analysis algorithm runs within the server, and if the baby is crying a lot at night, for example, it generates advice such as "play music at a steady rhythm."

[1176] Step 4:

[1177] The server notifies the user of the generated parenting advice via a smartphone application. Input: Parenting advice, Output: Parenting advice displayed on the smartphone. Specifically, the server sends a notification to the user's smartphone, and the advice is displayed in the app's notification center or pop-up.

[1178] Step 5:

[1179] The device monitors the newborn's abnormal movements and sounds, and if an abnormality is detected, it immediately notifies the server. The server analyzes the abnormal data and, if it determines that there is an emergency, automatically notifies the designated emergency contacts. Input: Abnormal movement and sound data, Output: Emergency notification. Specifically, when an abnormality is detected, the device sends data to the server, and the server notifies the emergency contacts by phone or SMS.

[1180] Step 6:

[1181] When the user reaches the next growth stage, the server sends the user a notification to migrate to a new device. The user accepts and configures the new device. When the device is connected, the server migrates all personal data to the new device. Input: Information about the new device, Output: Data migrated to the new device. Specifically, the user connects the new device to Wi-Fi and sends information to the server, and the server copies the original data to the new device.

[1182] Step 7:

[1183] The server provides parenting advice tailored to the newborn's developmental stage and emergency response measures. Input: Developmental stage information, Output: Advice and response measures according to the developmental stage. Specifically, the server compares the data with past data to determine the developmental stage, generates the necessary parenting advice and emergency response measures, and notifies the app.

[1184] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1185] The following system and its processing will be described as an embodiment of the present invention. This system provides optimized services by replacing devices according to the needs of a user as they grow from newborn, while inheriting personal data. Furthermore, it includes an emotion engine that recognizes the user's emotions and adjusts advice based on those emotions.

[1186] Overall system configuration

[1187] The system consists of the following main components:

[1188] 1. A way to enter basic information about newborns

[1189] 2. A means of collecting data by monitoring the movements and sounds of newborns

[1190] 3. A means of analyzing collected data and providing advice to users

[1191] 4. Means of emergency contact when an abnormality is detected

[1192] 5. A way to transfer data to the next device as users grow

[1193] 6. Emotion engine that recognizes user emotions

[1194] 7. Means for analyzing the emotional data recognized by the emotion engine and adjusting the advice

[1195] Each element is specifically implemented as follows:

[1196] A means of entering basic information about a newborn

[1197] For the initial setup, the user uses a smartphone app to enter basic information such as the newborn's name, date of birth, and gender. The device receives this information, sends it to a server, and stores it in a database. This information forms the basis for personalization in all subsequent processes.

[1198] A means of monitoring and collecting data on newborn movements and sounds

[1199] The device uses a camera and microphone to monitor the newborn's movements and sounds 24 / 7, including the baby's crying, sleep patterns, and body movements, and the collected data is sent to a server in real time.

[1200] A means of analyzing collected data and providing advice to users

[1201] The server analyzes the collected data and models the newborn's daily rhythm and characteristics. Based on the analysis results, it generates specific childcare advice for the user. For example, if a baby frequently cries at night, the server will provide the user with advice such as "play music at a steady rhythm." The device then notifies the user of this advice via a smartphone app.

[1202] A means of making emergency contact when an abnormality is detected

[1203] The device detects abnormal movements or sounds from the newborn. The server analyzes the abnormal data, determines whether it is an emergency, and automatically sends an emergency notification to designated contacts (e.g., emergency services, parents). The user receives the emergency notification via a smartphone app, allowing them to respond quickly.

[1204] A way to transfer data to the next device as users grow

[1205] When the user turns two years old, the server sends a notification to transition to a device suitable for the next stage of development. The user purchases a new device and sets it up. The device establishes the new device's Wi-Fi settings and connects to the server. The server transfers all personal data to the new device and continues to provide consistent support.

[1206] Emotion engine that recognizes user emotions

[1207] The device uses a camera and voice recognition technology to analyze the user's facial expressions and tone of voice, and an emotion engine to recognize the user's emotions, allowing it to more accurately understand the baby's needs and discomfort.

[1208] A means of analyzing the emotional data recognized by the emotion engine and adjusting the advice

[1209] The server analyzes the emotional data collected by the emotion engine to assess the user's current emotional state. For example, if the server determines that the user is under stress, it will provide special care advice. This advice is dynamically adjusted according to the user's emotional state, enabling more personalized care.

[1210] Processing explanation in natural language with concrete examples

[1211] For example, when a user enters basic information about a newborn into a smartphone app, the device sends this information to a server and stores it in a database. The device then uses a camera and microphone to monitor the baby's movements and sounds 24 / 7. The collected data is sent to the server in real time, which analyzes it. For example, if the server detects that the baby is crying frequently at night, it will notify the user through the smartphone app with advice to "play music at a regular rhythm." Furthermore, if the device detects abnormal movements or sounds from the baby, the server will determine this is an emergency and automatically contact emergency services. Finally, when the user turns two years old, the server will transfer the data to a new device, providing consistent support for childcare.

[1212] By introducing the emotion engine, it becomes possible to more accurately grasp the baby's emotional state and provide appropriate care. For example, if the server recognizes that the baby is feeling strong anxiety in a particular situation, it will provide special advice to the user to provide a sense of security. In this way, the emotion engine realizes optimal support according to the user's emotions.

[1213] The processing flow will be explained below.

[1214] Step 1:

[1215] The user opens the smartphone app and connects the new monitoring camera device to Wi-Fi.

[1216] Step 2:

[1217] The device checks the Internet connection and performs a connection test to the server.

[1218] Step 3:

[1219] The server verifies the connection and sends the settings screen to the user.

[1220] Step 4:

[1221] The user enters basic information about the newborn baby, such as their name, date of birth, and gender, on the app's settings screen.

[1222] Step 5:

[1223] The terminal receives the information entered by the user and transmits it to the server.

[1224] Step 6:

[1225] The server stores the received information in a database.

[1226] Step 7:

[1227] The device uses a camera and microphone to monitor the newborn's movements and sounds 24 hours a day.

[1228] Step 8:

[1229] The data collected by the device is sent to the server in real time.

[1230] Step 9:

[1231] The server receives the data and performs pre-processing (noise removal, time synchronization, etc.).

[1232] Step 10:

[1233] The server analyzes the preprocessed data and models the newborn's daily rhythms and characteristics.

[1234] Step 11:

[1235] The server generates specific child-rearing advice based on the analysis results.

[1236] Step 12:

[1237] The server notifies the user of the generated advice.

[1238] Step 13:

[1239] The device displays a notification to the user via a smartphone app, saying, "The baby has started crying. Please play music."

[1240] Step 14:

[1241] The user confirms the notification and starts playing music in the app.

[1242] Step 15:

[1243] The device will play music and continue to monitor your baby's condition.

[1244] Step 16:

[1245] The device detects abnormal movements or sounds from the baby.

[1246] Step 17:

[1247] Any abnormality information detected by the device is immediately sent to the server.

[1248] Step 18:

[1249] The server analyzes the abnormal data and determines whether it is an emergency.

[1250] Step 19:

[1251] If the server determines that an emergency exists, it will automatically send an emergency notification to the designated contacts.

[1252] Step 20:

[1253] The device sends an emergency notification to the user, displaying the message "Your baby is in danger. Call an ambulance."

[1254] Step 21:

[1255] Users can check emergency notifications and take appropriate action immediately.

[1256] Step 22:

[1257] The server sends a notification to the user to transition to a new device when the user turns two years old.

[1258] Step 23:

[1259] The device will display a message saying "Please move to the next stage device" and provide guidelines.

[1260] Step 24:

[1261] A user purchases a new device and sets it up for initial setup.

[1262] Step 25:

[1263] The device establishes a Wi-Fi connection for the new device and connects to the server.

[1264] Step 26:

[1265] The server will transfer all existing data to the new device.

[1266] Step 27:

[1267] The device receives the migrated data and starts new support tailored to the growing user base.

[1268] Step 28:

[1269] The server analyzes the monitoring data from the new device and continues to provide consistent parenting support.

[1270] Step 29:

[1271] The device uses a camera and microphone to collect the user's facial expressions and tone of voice.

[1272] Step 30:

[1273] The data collected by the device is sent to the server in real time.

[1274] Step 31:

[1275] The server uses an emotion engine to analyze the collected data and recognize the user's emotional state.

[1276] Step 32:

[1277] The server adjusts the parenting advice based on the emotional data.

[1278] Step 33:

[1279] The server notifies the user of the adjusted advice.

[1280] Step 34:

[1281] The device displays a message via a smartphone app saying, "Your baby seems anxious. Please hold him."

[1282] Step 35:

[1283] The user sees the notification and takes the appropriate action.

[1284] Example 2

[1285] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1286] Modern childcare demands personalized services that meet the needs of children from newborn to adulthood. However, conventional systems have struggled to provide services while consistently transferring data and replacing devices appropriately as users grow. Recognizing users' emotions and providing appropriate advice is also a challenge. Furthermore, systems lacked the ability to quickly and automatically contact emergency personnel when an abnormality was detected.

[1287] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1288] In this invention, the server includes means for inputting basic information about the user, means for collecting data by monitoring the user's movements and voice, means for analyzing the collected data and providing advice to the user, means for making emergency contact when an abnormality is detected, means for transferring data to a subsequent device in accordance with the user's growth, an emotion engine for recognizing the user's emotions, and means for analyzing the emotion data recognized by the emotion engine and adjusting advice. This enables device replacement and data transfer in accordance with the user's growth, provision of personalized services based on emotions, and rapid emergency response.

[1289] The term "user" refers to a person who uses the system, and in the present invention refers to all users including newborns and their growing children.

[1290] The term "device" refers to all hardware devices used in the system of the present invention, including monitoring devices, recording devices, communication devices, and the like.

[1291] "Basic Information" refers to the default information about a User, including personally identifiable information such as name, date of birth, and gender.

[1292] "Means for monitoring movements and sounds" refers to the function of recording and collecting user actions and sounds in real time using input devices such as cameras and microphones.

[1293] "Data collection means" means any process or device that temporarily or permanently stores information such as a user's movements or voice.

[1294] "Means for analyzing data" refers to functions, including software and algorithms, that analyze collected data and identify specific patterns or trends.

[1295] "Means for providing advice" means a system function for making suggestions to users regarding childcare and health management based on the analysis results.

[1296] "Means for making emergency contact" refers to the function of promptly sending warnings or notifications to the user or designated third parties via communication means when an abnormality is detected.

[1297] "Means for transferring data" refers to the ability to transfer data from an old device to a new device as the user grows.

[1298] "Emotion-aware emotion engine" means specialized algorithms and software that analyze a user's facial expressions and tone of voice to recognize their emotional state.

[1299] "Means for analyzing emotional data and adjusting advice" refers to the function of appropriately adjusting the content of advice based on emotional data recognized by the emotion engine, thereby providing a more personalized service.

[1300] The system of the present invention aims to provide personalized services through device replacement, data transfer, and emotion recognition in accordance with the user's growth. This system is composed of multiple hardware and software components, the role of which is described in detail below.

[1301] Overall system configuration

[1302] The system consists of the following main components:

[1303] 1. A way to enter basic user information

[1304] 2. Collecting data by monitoring your movements and voice

[1305] 3. A means of analyzing collected data and providing advice to users

[1306] 4. Means of emergency contact when an abnormality is detected

[1307] 5. A way to transfer data to the next device as the user grows

[1308] 6. Emotion engine that recognizes user emotions

[1309] 7. Means for analyzing the emotional data recognized by the emotion engine and adjusting the advice

[1310] A means of entering basic user information

[1311] For initial setup, the user uses a smartphone application to enter basic information such as the user's name, date of birth, gender, etc. The device receives this information, sends it to the server, and stores it in a database. This information forms the basis for personalization in all subsequent processes.

[1312] A means of collecting data by monitoring user movements and voices

[1313] The device uses a camera and microphone to monitor the user's movements and voice 24 / 7, including movement patterns, tone of voice, facial expressions, etc. The collected data is sent to a server in real time.

[1314] A means of analyzing collected data and providing advice to users

[1315] The server analyzes the collected data and models the user's lifestyle and characteristics. Based on the analysis results, it generates specific advice for the user. For example, if the server recognizes that the user is feeling stressed, it will provide the advice "listen to music to relax." The device then notifies the user of this advice via a smartphone application.

[1316] A means of making emergency contact when an abnormality is detected

[1317] The device detects the user's abnormal movements or sounds. The server analyzes the abnormal data, determines that it is an emergency, and automatically sends an emergency notification to designated contacts (e.g., emergency contacts). The user receives the emergency notification through a smartphone application and can respond quickly.

[1318] A way to transfer data to the next device as the user grows

[1319] As a user grows, the server sends a migration notification to a device suitable for the next stage of growth. The user purchases a new device and performs initial setup. The device establishes the network settings for the new device and connects to the server. The server migrates all data to the new device and continues to provide consistent support.

[1320] Emotion engine that recognizes user emotions

[1321] The device uses a camera and voice recognition technology to analyze the user's facial expressions and tone of voice, and an emotion engine to recognize the user's emotions, allowing it to more accurately understand the user's needs and complaints.

[1322] A means of analyzing the emotional data recognized by the emotion engine and adjusting the advice

[1323] The server analyzes the emotion data collected by the emotion engine to assess the user's current emotional state. For example, if the server determines that the user is under stress, it provides special care advice. This advice is dynamically adjusted according to the user's emotional state, enabling more personalized care.

[1324] Processing explanation in natural language with concrete examples

[1325] For example, when a user enters basic information about a newborn into a smartphone app, the device sends this information to a server and stores it in a database. The device then uses a camera and microphone to monitor the baby's movements and sounds 24 / 7. The collected data is sent to the server in real time, which analyzes it. For example, if the server detects that the baby is crying frequently at night, it will notify the user through the smartphone app with advice to "play music at a regular rhythm." Furthermore, if the device detects abnormal movements or sounds from the baby, the server will determine this is an emergency and automatically contact emergency services. Finally, when the user turns two years old, the server will transfer the data to a new device, providing consistent childcare support.

[1326] Example prompts for generative AI models

[1327] "When a user uses a smartphone app to enter basic information about a newborn baby, please explain the specific processing steps of how that information is sent to the server and stored in the database."

[1328] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1329] Step 1:

[1330] The user launches a smartphone application and enters basic information about the newborn baby. The entered basic information includes the baby's name, date of birth, and gender. This information is collected within the application and sent to the device. The device converts this information into JSON format and sends it to the server using the HTTPS protocol. The server saves the received data in a database and returns a save completion response to the device.

[1331] Specific operation:

[1332] 1. The user opens the app's input form and enters the newborn's information.

[1333] 2. The device serializes the user input data into JSON.

[1334] 3. The device sends data to the server via HTTPS.

[1335] 4. The server validates the incoming data and saves it as a new record in the database.

[1336] 5. The server returns a save completion response to the terminal, and the terminal notifies the user.

[1337] Step 2:

[1338] The device monitors the user's movements and voice 24 / 7 using a camera and microphone. This monitoring captures the user's movement and voice patterns. This data is stored in a buffer at regular intervals and then securely transmitted to a server using a VPN.

[1339] Specific operation:

[1340] 1. The device begins capturing real-time data using the camera and microphone.

[1341] 2. Movement and audio data are temporarily stored in a buffer.

[1342] 3. At regular intervals, the contents of the buffer are sent to the server via VPN.

[1343] Step 3:

[1344] The server analyzes the received data and models the user's lifestyle and characteristics. The received data is processed by an analysis module to extract specific patterns and trends. This generates a user behavior model that is stored in a database.

[1345] Specific operation:

[1346] 1. The server passes the received data to a dedicated module that analyzes it.

[1347] 2. The analytics module runs algorithms that identify behavioral patterns and trends.

[1348] 3. Identified patterns and trends are modeled and stored in a database.

[1349] Step 4:

[1350] The server generates advice for the user based on the analysis results. The generated advice is notified to the user via a smartphone application. For example, if the server recognizes that the user is feeling stressed, it will provide the advice "listen to music to relax."

[1351] Specific operation:

[1352] 1. The server selects an advice template based on the analysis results.

[1353] 2. A specific message is generated based on the selected template.

[1354] 3. The generated advice is sent to the device, which then notifies the user via an app notification.

[1355] Step 5:

[1356] The device runs an algorithm to detect abnormal user movements or sounds. If an abnormality is detected, it sends an alert to the server. The server analyzes the alert data and, if an abnormality is detected, sends a notification to designated emergency contacts. The user receives the emergency notification through a smartphone application.

[1357] Specific operation:

[1358] 1. The device runs an anomaly detection algorithm that monitors real-time data.

[1359] 2. If an abnormality is detected, an alert is sent to the server immediately.

[1360] 3. The server analyzes the alert and, if it determines that there is an abnormality, sends a notification to the registered emergency contact.

[1361] 4. Users receive emergency notifications through the app and respond quickly.

[1362] Step 6:

[1363] The server sends migration notifications to new devices as users grow. The user purchases a new device and performs initial setup. The device establishes network settings for the new device and connects to the server. The server migrates all data to the new device and continues to provide consistent support.

[1364] Specific operation:

[1365] 1. The server monitors the user's growth data and generates migration notifications at appropriate times.

[1366] 2. The user purchases a new device and goes through the initial setup procedure.

[1367] 3. The device completes the network configuration of the new device and connects to the server.

[1368] 4. The server transfers the data from the old device to the new device.

[1369] Step 7:

[1370] The device uses a camera and voice recognition technology to analyze the user's facial expressions and tone of voice, and recognizes the user's emotions using an emotion engine. This data is sent to a server, which then analyzes it using the emotion engine. Based on the analysis results, tailored advice is provided to the user.

[1371] Specific operation:

[1372] 1. The device uses a camera and microphone to perform facial recognition and voice analysis.

[1373] 2. The analyzed data is sent to the server in real time.

[1374] 3. The server passes the data to the emotion engine to evaluate the user's emotional state.

[1375] 4. Based on the evaluation results, generate and notify tailored advice to the user.

[1376] (Application example 2)

[1377] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1378] While modern childcare demands personalized support tailored to each newborn's developmental stage, manual information management and decision-making are required, increasing the burden of childcare. It is also difficult to accurately grasp a newborn's emotional state and provide appropriate care based on that. Furthermore, childcare products and services are typically offered in brick-and-mortar stores, lacking personalization tailored to individual needs. This often results in inadequate childcare support.

[1379] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for inputting basic information about the newborn, a means for monitoring the newborn's movements and voice to collect data, a means for analyzing the collected data and providing advice to the user, a means for making an emergency call when an abnormality is detected, a means for recognizing the user's emotions and adjusting advice based on the emotion data, a means for transferring data to the next device as the user grows, and a means for proposing personalized products and services in physical stores and providing special care counseling. This enables seamless childcare support according to the newborn's growth stage, provision of appropriate care based on the newborn's emotional state, consistent data management, and provision of personalized services in physical stores according to individual needs.

[1380] "Means for inputting basic information about a newborn" is a function that allows a user to input basic information about a newborn, such as the name, date of birth, and gender, and send it to the server.

[1381] "Means for monitoring the movements and sounds of newborns and collecting data" refers to a function that uses cameras and microphones to monitor the movements and sounds of newborns 24 hours a day and collect data.

[1382] "Means for analyzing collected data and providing advice to users" refers to a function in which the server analyzes collected data, models the daily rhythms and characteristics of the newborn, and provides appropriate child-rearing advice to users.

[1383] "Means for making emergency contact when an abnormality is detected" is a function that allows the system to detect abnormal movements or sounds from the newborn and automatically notify emergency contacts.

[1384] "Means for recognizing the user's emotions and adjusting advice based on emotional data" refers to a function that uses an emotion engine to analyze the user's facial expressions and tone of voice and adjust advice to provide appropriate care.

[1385] "A way to transfer data to the next device as the user grows" is a feature that allows existing data to be transferred to a new device as the newborn grows, providing consistent parenting support.

[1386] "Means of proposing personalized products and services in physical stores and providing special care counseling" refers to a function that personalizes the proposal of childcare products and services in physical stores and provides care counseling according to individual needs.

[1387] The following system and its processing will be described as an embodiment of the present invention. This system provides optimized services by replacing devices according to the needs of a user as they grow from newborn, while inheriting personal data. Furthermore, it includes an emotion engine that recognizes the user's emotions and adjusts advice based on those emotions.

[1388] Overall system configuration

[1389] The system consists of the following main components:

[1390] 1. A way to enter basic information about newborns

[1391] 2. A means of collecting data by monitoring the movements and sounds of newborns

[1392] 3. A means of analyzing collected data and providing advice to users

[1393] 4. Means of emergency contact when an abnormality is detected

[1394] 5. A way to recognize user emotions and tailor recommendations based on emotional data

[1395] 6. A way to transfer data to the next device as users grow

[1396] 7. A way to offer personalized products and services in physical stores and provide special care counseling

[1397] A means of entering basic information about a newborn

[1398] For the initial setup, the user uses a smartphone app to enter basic information about the newborn, such as their name, date of birth, and gender. The device receives this information, sends it to a server, and stores it in a database. This information forms the basis for personalization in all subsequent processes.

[1399] A means of monitoring and collecting data on newborn movements and sounds

[1400] The device uses a camera and microphone to monitor the newborn's movements and sounds 24 / 7, including the baby's crying, sleep patterns, and body movements, and the collected data is sent to a server in real time.

[1401] A means of analyzing collected data and providing advice to users

[1402] The server analyzes the collected data and models the newborn's daily rhythm and characteristics. Based on the analysis results, it generates specific childcare advice for the user. For example, if a baby frequently cries at night, the server will provide the user with advice such as "play music at a steady rhythm." The device then notifies the user of this advice via a smartphone app.

[1403] A means of making emergency contact when an abnormality is detected

[1404] The device detects abnormal movements or sounds from the newborn. The server analyzes the abnormal data, determines whether it is an emergency, and automatically sends an emergency notification to designated contacts (e.g., ambulance, parents). The user receives the emergency notification through a smartphone app and can respond quickly.

[1405] A means of recognizing user emotions and tailoring advice based on emotional data

[1406] The device uses a camera and voice recognition technology to analyze the user's facial expressions and tone of voice, and recognizes the user's emotions using an emotion engine. This allows for more accurate understanding of the baby's needs and ailments. The server analyzes the emotion data collected by the emotion engine and evaluates the user's current emotional state. For example, if the server determines that the user is under stress, it will provide special care advice. This advice is dynamically adjusted according to the user's emotional state, enabling more personalized care.

[1407] A way to transfer data to the next device as users grow

[1408] When the user turns two years old, the server sends a notification to transition to a device suitable for the next stage of development. The user purchases a new device and sets it up. The device establishes the new device's Wi-Fi settings and connects to the server. The server transfers all personal data to the new device and continues to provide consistent support.

[1409] A means to offer personalized products and services in physical stores and provide special care counseling

[1410] There is a smartphone app that provides childcare products and services in brick-and-mortar stores, and the server proposes personalized products and services based on basic information about the newborn, their daily movements, and emotional data. The app also allows users to make reservations for care counseling sessions in brick-and-mortar stores and receive consultations in real time.

[1411] Specific examples

[1412] For example, when a user enters basic information about a newborn baby into a smartphone app, the device sends this information to a server and stores it in a database. The device then uses a camera and microphone to monitor the baby's movements and sounds 24 hours a day. The collected data is sent in real time to the server, which analyzes it. For example, if the server detects that the baby is crying frequently at night, it will notify the user through the smartphone app with advice to "play music at a regular rhythm."

[1413] By introducing the emotion engine, it becomes possible to more accurately grasp the baby's emotional state and provide appropriate care. For example, if the server recognizes that the baby is feeling strong anxiety in a particular situation, it will provide special advice to the user to provide a sense of security. In this way, the emotion engine realizes optimal support according to the user's emotions.

[1414] Example prompts for generative AI models

[1415] Generate the best advice for your crying baby based on the following data:

[1416] Basic information: Name "Newborn A", Date of birth "2022-01-01", Gender "Male"

[1417] Movement and sound data: "Frequent crying at night"

[1418] Emotion data: "crying face" and "anxious voice"

[1419] Output formats:

[1420] Advice: New Instructions

[1421] Additional Care Suggestions: Special Care Suggestions

[1422] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1423] Step 1:

[1424] The user enters basic information about the newborn into a smartphone app.

[1425] How it works: The user uses the app's input form to enter the newborn's name, date of birth, and gender, and the information is sent by the device to the server and stored in a database.

[1426] Input: Newborn's name, date of birth, sex

[1427] Output: Basic information of the newborn stored in the database

[1428] Step 2:

[1429] The device uses a camera and microphone to monitor the newborn's movements and sounds and collect data.

[1430] How it works: The device periodically activates the camera and microphone to monitor the newborn's movements and cries, and the collected data is sent to the server in real time.

[1431] Input: Video and audio data from the camera and microphone

[1432] Output: Monitoring data of the newborn's movements and voices sent to a server

[1433] Step 3:

[1434] The server analyzes the collected data and models the newborn's daily rhythms and characteristics.

[1435] How it works: The server analyzes the received data using machine learning algorithms to identify the time of day when the newborn is crying and their movement patterns.

[1436] Input: Neonatal movement and voice monitoring data

[1437] Output: Data modeling the daily rhythms and characteristics of newborns

[1438] Step 4:

[1439] The server generates parenting advice based on the analysis results and notifies the user via the device.

[1440] Specific operation: Based on the analysis data, the server creates parenting advice, such as "play music at a steady rhythm," and notifies the user via a smartphone app.

[1441] Input: Data modeling the daily rhythms and characteristics of newborns

[1442] Output: Parenting advice sent to a smartphone app

[1443] Step 5:

[1444] If the device detects any abnormal movements or sounds from the newborn, the server will automatically send an emergency notification.

[1445] Specific operation: When the device detects an abnormality, it sends the data to the server, which determines it is an emergency and automatically sends a notification to pre-defined emergency contacts.

[1446] Input: Unusual movement and audio data

[1447] Output:Notify emergency contacts

[1448] Step 6:

[1449] The device uses a camera and voice recognition technology to collect the user's emotional data, which is then analyzed by the server to tailor the advice.

[1450] How it works: The device uses a camera to capture the user's facial expressions and a microphone to analyze the tone of voice. The collected emotional data is sent to the server, which then adjusts the advice based on the user's emotional state.

[1451] Input: Emotion data from camera and microphone

[1452] Output: Advice based on emotional state

[1453] Step 7:

[1454] As the user grows, the server sends a notification for the next device migration and transfers the data to the new device.

[1455] What it does: When a user purchases and sets up a new device, the device establishes the device's Wi-Fi settings and connects to the server, which then transfers all personal data to the new device.

[1456] Input: New device setup information

[1457] Output: Personal data transferred to new device

[1458] Step 8:

[1459] Servers will suggest personalized products and services in physical stores and provide special care counseling.

[1460] How it works: The server recommends optimal products and services at physical stores based on the newborn's basic information, daily movements, and emotional data. The app also allows users to make appointments for special care counseling.

[1461] Input: Basic information of newborn baby, movement and voice data, emotion data

[1462] Output: Personalized recommendations and care counseling in physical stores

[1463] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1464] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1465] 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 the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1466] [Fourth embodiment]

[1467] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1468] 7, a 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.

[1469] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1470] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1471] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1472] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1473] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1474] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1475] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1476] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1477] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1478] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1479] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1480] The following system and its processing will be described as an embodiment of the present invention. This system provides optimized services by replacing devices according to the needs of users growing from newborns, while inheriting personal data.

[1481] Overall system configuration

[1482] The system consists of the following main components:

[1483] 1. A way to enter basic information about newborns

[1484] 2. A means of collecting data by monitoring the movements and sounds of newborns

[1485] 3. A means of analyzing collected data and providing advice to users

[1486] 4. Means of emergency contact when an abnormality is detected

[1487] 5. A way to transfer data to the next device as users grow

[1488] Each element is specifically implemented as follows:

[1489] A means of entering basic information about a newborn

[1490] For the initial setup, the user uses a smartphone app to enter basic information such as the newborn's name, date of birth, and gender. The device receives this information, sends it to a server, and stores it in a database. This information forms the basis for personalization in all subsequent processes.

[1491] A means of monitoring and collecting data on newborn movements and sounds

[1492] The device uses a camera and microphone to monitor the newborn's movements and sounds 24 / 7, including the baby's crying, sleep patterns, and body movements, and the collected data is sent to a server in real time.

[1493] A means of analyzing collected data and providing advice to users

[1494] The server analyzes the collected data and models the newborn's daily rhythm and characteristics. Based on the analysis results, it generates specific childcare advice for the user. For example, if a baby frequently cries at night, the server will provide the user with advice such as "play music at a steady rhythm." The device then notifies the user of this advice via a smartphone app.

[1495] A means of making emergency contact when an abnormality is detected

[1496] The device detects abnormal movements or sounds from the newborn. The server analyzes the abnormal data, determines whether it is an emergency, and automatically sends an emergency notification to designated contacts (e.g., emergency services, parents). The user receives the emergency notification via a smartphone app, allowing them to respond quickly.

[1497] A way to transfer data to the next device as users grow

[1498] When the user turns two years old, the server sends a notification to transition to a device suitable for the next stage of development. The user purchases a new device and sets it up. The device establishes the new device's Wi-Fi settings and connects to the server. The server transfers all personal data to the new device and continues to provide consistent support.

[1499] Processing explanation in natural language with concrete examples

[1500] For example, when a user enters basic information about a newborn into a smartphone app, the device sends this information to a server and stores it in a database. The device then uses a camera and microphone to monitor the baby's movements and sounds 24 / 7. The collected data is sent to the server in real time, which analyzes it. For example, if the server detects that the baby is crying frequently at night, it will notify the user through the smartphone app with advice to "play music at a regular rhythm." Furthermore, if the device detects abnormal movements or sounds from the baby, the server will determine this is an emergency and automatically contact emergency services. Finally, when the user turns two years old, the server will transfer the data to a new device, providing consistent support for childcare.

[1501] This allows users to receive consistent support as their child grows from birth, reducing the burden of childcare.

[1502] The processing flow will be explained below.

[1503] Step 1:

[1504] The user opens the smartphone app and connects the new monitoring camera device to Wi-Fi.

[1505] Step 2:

[1506] The device checks the Internet connection and performs a connection test to the server.

[1507] Step 3:

[1508] The server verifies the connection and sends the settings screen to the user.

[1509] Step 4:

[1510] The user enters basic information about the newborn baby, such as their name, date of birth, and gender, on the app's settings screen.

[1511] Step 5:

[1512] The terminal receives the information entered by the user and transmits it to the server.

[1513] Step 6:

[1514] The server stores the received information in a database.

[1515] Step 7:

[1516] The device uses a camera and microphone to monitor the newborn's movements and sounds 24 hours a day.

[1517] Step 8:

[1518] The data collected by the device is sent to the server in real time.

[1519] Step 9:

[1520] The server receives the data and performs pre-processing (noise removal, time synchronization, etc.).

[1521] Step 10:

[1522] The server analyzes the preprocessed data and models the newborn's daily rhythms and characteristics.

[1523] Step 11:

[1524] The server generates specific child-rearing advice based on the analysis results.

[1525] Step 12:

[1526] The server notifies the user of the generated advice.

[1527] Step 13:

[1528] The device displays a notification to the user via a smartphone app, saying, "The baby has started crying. Please play music."

[1529] Step 14:

[1530] The user confirms the notification and starts playing music in the app.

[1531] Step 15:

[1532] The device will play music and continue to monitor your baby's condition.

[1533] Step 16:

[1534] The device detects abnormal movements or sounds from the baby.

[1535] Step 17:

[1536] Any abnormality information detected by the device is immediately sent to the server.

[1537] Step 18:

[1538] The server analyzes the abnormal data and determines whether it is an emergency.

[1539] Step 19:

[1540] If the server determines that an emergency exists, it will automatically send an emergency notification to the designated contacts.

[1541] Step 20:

[1542] The device sends an emergency notification to the user, displaying the message "Your baby is in danger. Call an ambulance."

[1543] Step 21:

[1544] Users can check emergency notifications and take appropriate action immediately.

[1545] Step 22:

[1546] The server sends a notification to the user to transition to a new device when the user turns two years old.

[1547] Step 23:

[1548] The device will display a message saying "Please move to the next stage device" and provide guidelines.

[1549] Step 24:

[1550] A user purchases a new device and sets it up for initial setup.

[1551] Step 25:

[1552] The device establishes a Wi-Fi connection for the new device and connects to the server.

[1553] Step 26:

[1554] The server will transfer all existing data to the new device.

[1555] Step 27:

[1556] The device receives the migrated data and starts new support tailored to the growing user base.

[1557] Step 28:

[1558] The server analyzes the monitoring data from the new device and continues to provide consistent parenting support.

[1559] Example 1

[1560] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1561] Conventional childcare support systems have the problem of making it difficult to properly replace devices and transfer data as the baby grows from birth. Furthermore, data collection, analysis, and advice provision of newborn movements and voices are often inconsistent, making it difficult to respond quickly in emergencies. This creates the problem of parents being unable to receive consistent childcare support and increasing the burden of childcare on parents.

[1562] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1563] In this invention, the server includes means for inputting basic information, means for monitoring movements and sounds and collecting data, means for analyzing the collected data and providing advice, means for making emergency contact when an abnormality is detected, means for transferring data to the next device as the user grows, means for analyzing the collected data using a machine learning model and modeling daily rhythms and characteristics, and means for automatically making emergency contact and notifying designated contacts. This enables consistent childcare support according to the user's stage of growth and reduces the burden on parents.

[1564] "Basic information" refers to information about the user that is necessary for initial setup, such as name, date of birth, and gender.

[1565] "Movement and sound" refers to data on the newborn's body movements, cries, and other vocalizations.

[1566] The "means of collecting data" refers to the method of using a camera and microphone to monitor the newborn's movements and sounds and collecting this data on a terminal.

[1567] "Means for analyzing collected data" refers to methods for analyzing the daily rhythms and characteristics of newborns using collected data, and in particular, machine learning models are often used to perform highly accurate analysis.

[1568] The "means for providing advice" is a method for generating and notifying specific child-rearing advice to the user based on the analysis results.

[1569] "Means for detecting abnormalities" refers to a method of constantly monitoring the movements and sounds of the newborn and detecting any abnormal patterns.

[1570] "Means for making emergency contact" refers to a method for automatically sending a notification to designated contacts when an abnormality is detected.

[1571] "Means for transferring data" refers to a method for transferring data from a newborn to a new device suitable for the next stage of development.

[1572] "Machine learning model" refers to the algorithms and techniques used for analysis and modeling using collected data.

[1573] "Designated Contact" means the contact information for a parent, emergency services, or other person who should be contacted in an emergency.

[1574] Overall system configuration

[1575] This system allows users to exchange terminals as they grow, and provides consistent services while transferring data. The main elements of the system and their processing are explained below.

[1576] Enter basic information

[1577] For the initial setup, the user uses a smartphone application to enter basic information about the newborn, such as their name, date of birth, and gender. This information is then encrypted and sent from the device to a server, which stores it in a database, allowing for any necessary personalization during subsequent processes.

[1578] Data collection

[1579] The device uses a camera and microphone to monitor the newborn's movements and voice in real time. Specifically, the camera tracks the baby's position and movements, and the microphone detects crying and other sounds. This data is periodically sent to a server for real-time data collection.

[1580] Data analysis

[1581] The server analyzes the collected data. Generative AI models are used to achieve highly accurate data analysis. This analysis allows the newborn's daily rhythms and characteristics to be modeled. For example, the server analyzes the baby's sleep patterns and crying frequency to identify outliers and general trends.

[1582] Providing advice

[1583] Based on the analysis results, the server generates specific childcare advice. High-precision advice is generated using a generative AI model. For example, if a baby frequently cries at night, the server will advise the user to "play music at a steady rhythm." The device then notifies the user of this advice via a smartphone app.

[1584] Anomaly detection and emergency contact

[1585] The device monitors the newborn's movements and sounds in real time. If an abnormality is detected, the device sends the information to a server. The server analyzes the received data and determines whether it is an emergency. In the event of an emergency, an emergency notification is automatically sent to designated contacts (e.g., parents, emergency services). Users can also receive emergency notifications through a smartphone app, enabling a prompt response.

[1586] Data transfer

[1587] As the user grows, for example, when they reach the age of two, the server sends them a notification to transition to a device suitable for their new stage of development. The user purchases a new device and performs initial setup, such as Wi-Fi settings. Once the device has completed the new device setup, the server transfers all personal data to the new device. This ensures consistent support for the new device.

[1588] Examples and prompts

[1589] For example, when a user enters basic information about a newborn baby into a smartphone app, the device sends it to a server and stores it in a database. The device uses a camera and microphone to monitor the baby's movements and sounds, sending the data to the server in real time. The server analyzes the data and generates advice such as "playing music at a steady rhythm" if the baby is crying frequently at night. In an emergency, emergency services will be automatically contacted. When the user reaches a new developmental stage, the data is transferred to a new device.

[1590] Specific prompt examples:

[1591] "How to build a system that analyzes a baby's sleep patterns and generates and notifies appropriate childcare advice"

[1592] As described above, this system provides users with consistent childcare support and provides concrete measures to reduce the burden of childcare.

[1593] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1594] Step 1: Enter basic information

[1595] The user opens the application on their smartphone and enters basic information about the newborn, such as the newborn's name, date of birth, and gender. The device encrypts this information and sends it to the server, which then stores the received information in a database. The input is the newborn's basic information, such as the newborn's name, date of birth, and gender, entered by the user, and the output is that this information is accurately stored in the database.

[1596] Step 2: Collect data

[1597] The device uses a camera and microphone to monitor the newborn's movements and voice 24 hours a day. The camera captures the baby's position and movements, while the microphone collects crying and other sounds. This data is sent from the device to a server in real time. The input is the newborn's real-time movements and voice data, and the output is sent appropriately to the server.

[1598] Step 3: Analyze the data

[1599] The server analyzes the collected data. It uses a generative AI model to perform highly accurate data analysis and model the newborn's daily rhythms and characteristics. The analyzed data includes the baby's sleep patterns and crying frequency. The server uses a machine learning model to extract outliers and general trends and outputs them as the analysis results. The input is movement and audio data transmitted in real time, and the output is the modeled analysis results.

[1600] Step 4: Providing advice

[1601] The server generates specific childcare advice based on the analysis results. The advice is created using a generative AI model and notified to the user via the device. For example, if a baby frequently cries at night, the server will generate advice such as "play music at a steady rhythm." The input is the result of data analysis, and the output is a notification of specific childcare advice.

[1602] Step 5: Anomaly detection and emergency notification

[1603] The device monitors the newborn's abnormal movements and sounds in real time. If any suspicious movements are detected, the device sends the information to a server. The server analyzes the abnormal data and determines whether it is an emergency. If an emergency is determined, an emergency notification is automatically sent to designated contacts. The user can also receive the emergency notification through a smartphone application. The input is real-time data for detecting an abnormality, and the output is a notification to contact the emergency services.

[1604] Step 6: Transfer data

[1605] As the user grows, for example, when they reach the age of two, the server sends them a notification to migrate to a device suitable for their new stage of development. The user purchases a new device and performs initial setup such as Wi-Fi settings. Once the device completes the new device setup, the server migrates all personal data to the new device. This provides consistent support on the new device. The input is the migration instruction for the new device, and the output is the migrated data.

[1606] (Application example 1)

[1607] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1608] Conventional newborn monitoring systems struggle to provide appropriate devices and services for newborns as they grow. They also lack sufficient emergency response and childcare advice tailored to the newborn's development. This results in users having to purchase individual devices or use different systems, increasing the burden of childcare. Furthermore, while rapid and appropriate responses are required when an abnormality is detected, such systems are limited. An effective system that solves these problems is needed.

[1609] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1610] In this invention, the server includes means for inputting basic information about the newborn, means for monitoring the newborn's movements and voices and collecting data, means for analyzing the collected data and providing advice to the user, means for making emergency contact when an abnormality is detected, means for transferring data to the next device as the user grows, means for providing childcare advice and emergency response measures according to the newborn's stage of growth, and means for transmitting monitored data to the server in real time, thereby enabling consistent childcare support according to the newborn's stage of growth and rapid response to abnormalities.

[1611] "Replacing devices as users grow" means replacing appropriate hardware or software devices with new ones to provide the features and services required by users as they grow.

[1612] "Data transfer" refers to the consistent transfer of all personal data from an old device to a new device, ensuring that users continue to receive seamless services.

[1613] "Means for inputting basic information about a newborn" refers to a means for using a user interface such as a smartphone or computer to input initial information such as the newborn's name, date of birth, and gender, and registering it in the system.

[1614] "Means for monitoring the movements and sounds of newborns and collecting data" refers to means for using sensors such as cameras and microphones to monitor the movements and sounds of newborns in real time and collect this data.

[1615] The "means for analyzing collected data and providing advice to users" refers to means that has the function of analyzing data sent to the server, generating specific advice regarding child-rearing, and providing it to users.

[1616] "Means for making emergency contact when an abnormality is detected" refers to a means for automatically sending a notification to a designated emergency contact if an abnormality is detected in the newborn's movements or voice.

[1617] "Means for transferring data to the next device as the user grows" refers to a means for transferring all personal data to an appropriate new device as the user grows, thereby enabling uninterrupted service provision.

[1618] "Means for providing childcare advice and emergency response measures according to the user's stage of development" refers to means that have the function of automatically generating and providing appropriate childcare advice and emergency response measures according to the user's age and stage of development.

[1619] The "means for transmitting monitoring data to a server in real time" refers to a means for transmitting monitoring data of the newborn's movements and voice to a server in real time via the Internet, enabling immediate processing and analysis.

[1620] The following system and its processing will be described as an embodiment of the present invention. This system provides optimal services by replacing devices as users grow and transferring data.

[1621] Overall system configuration

[1622] The system consists of the following main components:

[1623] 1. A way to enter basic information about newborns

[1624] 2. A means of collecting data by monitoring the movements and sounds of newborns

[1625] 3. A means of analyzing collected data and providing advice to users

[1626] 4. Means of emergency contact when an abnormality is detected

[1627] 5. A way to transfer data to the next device as users grow

[1628] 6. A means of providing stage-appropriate parenting advice and emergency response plans

[1629] 7. A means of sending monitoring data to the server in real time

[1630] A means of entering basic information about a newborn

[1631] For the initial setup, the user uses a smartphone application to enter basic information about the newborn, such as their name, date of birth, and gender. The device receives this information, sends it to a server, and stores it in a database. This information forms the basis for personalization in all subsequent processes.

[1632] A means of monitoring and collecting data on newborn movements and sounds

[1633] The device uses a camera and microphone to monitor the newborn's movements and sounds 24 / 7, including the baby's crying, sleep patterns, and body movements, and the collected data is sent to a server in real time.

[1634] A means of analyzing collected data and providing advice to users

[1635] The server analyzes the collected data and models the newborn's daily rhythm and characteristics. Based on the analysis results, it generates specific childcare advice for the user. For example, if a baby frequently cries at night, the server will provide the user with advice such as "play music at a steady rhythm." The device then notifies the user of this advice via a smartphone app.

[1636] A means of making emergency contact when an abnormality is detected

[1637] The device detects any abnormal movements or sounds from the newborn. The server analyzes the abnormal data, determines whether an emergency has occurred, and automatically sends an emergency notification to designated contacts. The user receives the emergency notification via a smartphone app, allowing them to respond quickly.

[1638] A way to transfer data to the next device as users grow

[1639] When a user reaches the next growth stage, the server sends a notification to migrate to a new device. The user sets up the next device, and the device establishes the new device's Wi-Fi settings and connects to the server. The server then migrates all personal data to the new device, providing consistent support.

[1640] A means of providing stage-specific parenting advice and emergency response plans

[1641] The server generates childcare advice and emergency response measures that are tailored to the newborn's development. For example, if it detects the baby's crying, it will send an alarm to the user, telling them to "check if the baby's temperature is normal." It also provides advice on vaccination schedules and nutrition for each stage of the baby's development.

[1642] A means of sending monitoring data to a server in real time

[1643] The monitoring data is sent to a server in real time. The server immediately processes the received data and responds immediately if an abnormality occurs. This real-time processing enables prompt and appropriate childcare support.

[1644] Adding specific examples

[1645] For example, when a user enters basic information about a newborn into a smartphone app, the system sends this information to the server and stores it in a database. When the device detects the baby's crying, the server analyzes the data and sends a notification to the user, asking them to check if the baby's temperature is normal.

[1646] Example prompts to input to the generative AI model

[1647] "Generate tips on how to deal with a crying baby at night."

[1648] "Detect baby cries and provide emergency response based on that."

[1649] "Please tell me in detail how to provide first aid if a newborn baby's temperature suddenly rises."

[1650] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1651] Step 1:

[1652] The user uses a smartphone application to enter basic information such as the newborn's name, date of birth, and gender. The information entered by the user is sent from the smartphone application to the server and stored in a database. At this stage, input: basic information (name, date of birth, gender), output: basic information stored in the database. Specifically, when the user enters the required information into the application form and presses the "Submit" button, the data is sent to the server.

[1653] Step 2:

[1654] The device uses a camera and microphone to monitor the newborn's movements and voice 24 hours a day. The collected data is sent to a server in real time. Input: Newborn's movements and voice data, Output: Monitoring data sent to the server. Specifically, the device's built-in camera and microphone continuously capture video and audio, and send this data to the server via the network.

[1655] Step 3:

[1656] The server analyzes the received monitoring data and models the newborn's daily rhythms and behavioral patterns. Based on the analysis results, it generates specific child-rearing advice. Input: Monitoring data, Output: Child-rearing advice. Specifically, a data analysis algorithm runs within the server, and if the baby is crying a lot at night, for example, it generates advice such as "play music at a steady rhythm."

[1657] Step 4:

[1658] The server notifies the user of the generated parenting advice via a smartphone application. Input: Parenting advice, Output: Parenting advice displayed on the smartphone. Specifically, the server sends a notification to the user's smartphone, and the advice is displayed in the app's notification center or pop-up.

[1659] Step 5:

[1660] The device monitors the newborn's abnormal movements and sounds, and if an abnormality is detected, it immediately notifies the server. The server analyzes the abnormal data and, if it determines that there is an emergency, automatically notifies the designated emergency contacts. Input: Abnormal movement and sound data, Output: Emergency notification. Specifically, when an abnormality is detected, the device sends data to the server, and the server notifies the emergency contacts by phone or SMS.

[1661] Step 6:

[1662] When the user reaches the next growth stage, the server sends the user a notification to migrate to a new device. The user accepts and configures the new device. When the device is connected, the server migrates all personal data to the new device. Input: Information about the new device, Output: Data migrated to the new device. Specifically, the user connects the new device to Wi-Fi and sends information to the server, and the server copies the original data to the new device.

[1663] Step 7:

[1664] The server provides parenting advice tailored to the newborn's developmental stage and emergency response measures. Input: Developmental stage information, Output: Advice and response measures according to the developmental stage. Specifically, the server compares the data with past data to determine the developmental stage, generates the necessary parenting advice and emergency response measures, and notifies the app.

[1665] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1666] The following system and its processing will be described as an embodiment of the present invention. This system provides optimized services by replacing devices according to the needs of a user as they grow from newborn, while inheriting personal data. Furthermore, it includes an emotion engine that recognizes the user's emotions and adjusts advice based on those emotions.

[1667] Overall system configuration

[1668] The system consists of the following main components:

[1669] 1. A way to enter basic information about newborns

[1670] 2. A means of collecting data by monitoring the movements and sounds of newborns

[1671] 3. A means of analyzing collected data and providing advice to users

[1672] 4. Means of emergency contact when an abnormality is detected

[1673] 5. A way to transfer data to the next device as users grow

[1674] 6. Emotion engine that recognizes user emotions

[1675] 7. Means for analyzing the emotional data recognized by the emotion engine and adjusting the advice

[1676] Each element is specifically implemented as follows:

[1677] A means of entering basic information about a newborn

[1678] For the initial setup, the user uses a smartphone app to enter basic information such as the newborn's name, date of birth, and gender. The device receives this information, sends it to a server, and stores it in a database. This information forms the basis for personalization in all subsequent processes.

[1679] A means of monitoring and collecting data on newborn movements and sounds

[1680] The device uses a camera and microphone to monitor the newborn's movements and sounds 24 / 7, including the baby's crying, sleep patterns, and body movements, and the collected data is sent to a server in real time.

[1681] A means of analyzing collected data and providing advice to users

[1682] The server analyzes the collected data and models the newborn's daily rhythm and characteristics. Based on the analysis results, it generates specific childcare advice for the user. For example, if a baby frequently cries at night, the server will provide the user with advice such as "play music at a steady rhythm." The device then notifies the user of this advice via a smartphone app.

[1683] A means of making emergency contact when an abnormality is detected

[1684] The device detects abnormal movements or sounds from the newborn. The server analyzes the abnormal data, determines whether it is an emergency, and automatically sends an emergency notification to designated contacts (e.g., emergency services, parents). The user receives the emergency notification via a smartphone app, allowing them to respond quickly.

[1685] A way to transfer data to the next device as users grow

[1686] When the user turns two years old, the server sends a notification to transition to a device suitable for the next stage of development. The user purchases a new device and sets it up. The device establishes the new device's Wi-Fi settings and connects to the server. The server transfers all personal data to the new device and continues to provide consistent support.

[1687] Emotion engine that recognizes user emotions

[1688] The device uses a camera and voice recognition technology to analyze the user's facial expressions and tone of voice, and an emotion engine to recognize the user's emotions, allowing it to more accurately understand the baby's needs and discomfort.

[1689] A means of analyzing the emotional data recognized by the emotion engine and adjusting the advice

[1690] The server analyzes the emotional data collected by the emotion engine to assess the user's current emotional state. For example, if the server determines that the user is under stress, it will provide special care advice. This advice is dynamically adjusted according to the user's emotional state, enabling more personalized care.

[1691] Processing explanation in natural language with concrete examples

[1692] For example, when a user enters basic information about a newborn into a smartphone app, the device sends this information to a server and stores it in a database. The device then uses a camera and microphone to monitor the baby's movements and sounds 24 / 7. The collected data is sent to the server in real time, which analyzes it. For example, if the server detects that the baby is crying frequently at night, it will notify the user through the smartphone app with advice to "play music at a regular rhythm." Furthermore, if the device detects abnormal movements or sounds from the baby, the server will determine this is an emergency and automatically contact emergency services. Finally, when the user turns two years old, the server will transfer the data to a new device, providing consistent support for childcare.

[1693] By introducing the emotion engine, it becomes possible to more accurately grasp the baby's emotional state and provide appropriate care. For example, if the server recognizes that the baby is feeling strong anxiety in a particular situation, it will provide special advice to the user to provide a sense of security. In this way, the emotion engine realizes optimal support according to the user's emotions.

[1694] The processing flow will be explained below.

[1695] Step 1:

[1696] The user opens the smartphone app and connects the new monitoring camera device to Wi-Fi.

[1697] Step 2:

[1698] The device checks the Internet connection and performs a connection test to the server.

[1699] Step 3:

[1700] The server verifies the connection and sends the settings screen to the user.

[1701] Step 4:

[1702] The user enters basic information about the newborn baby, such as their name, date of birth, and gender, on the app's settings screen.

[1703] Step 5:

[1704] The terminal receives the information entered by the user and transmits it to the server.

[1705] Step 6:

[1706] The server stores the received information in a database.

[1707] Step 7:

[1708] The device uses a camera and microphone to monitor the newborn's movements and sounds 24 hours a day.

[1709] Step 8:

[1710] The data collected by the device is sent to the server in real time.

[1711] Step 9:

[1712] The server receives the data and performs pre-processing (noise removal, time synchronization, etc.).

[1713] Step 10:

[1714] The server analyzes the preprocessed data and models the newborn's daily rhythms and characteristics.

[1715] Step 11:

[1716] The server generates specific child-rearing advice based on the analysis results.

[1717] Step 12:

[1718] The server notifies the user of the generated advice.

[1719] Step 13:

[1720] The device displays a notification to the user via a smartphone app, saying, "The baby has started crying. Please play music."

[1721] Step 14:

[1722] The user confirms the notification and starts playing music in the app.

[1723] Step 15:

[1724] The device will play music and continue to monitor your baby's condition.

[1725] Step 16:

[1726] The device detects abnormal movements or sounds from the baby.

[1727] Step 17:

[1728] Any abnormality information detected by the device is immediately sent to the server.

[1729] Step 18:

[1730] The server analyzes the abnormal data and determines whether it is an emergency.

[1731] Step 19:

[1732] If the server determines that an emergency exists, it will automatically send an emergency notification to the designated contacts.

[1733] Step 20:

[1734] The device sends an emergency notification to the user, displaying the message "Your baby is in danger. Call an ambulance."

[1735] Step 21:

[1736] Users can check emergency notifications and take appropriate action immediately.

[1737] Step 22:

[1738] The server sends a notification to the user to transition to a new device when the user turns two years old.

[1739] Step 23:

[1740] The device will display a message saying "Please move to the next stage device" and provide guidelines.

[1741] Step 24:

[1742] A user purchases a new device and sets it up for initial setup.

[1743] Step 25:

[1744] The device establishes a Wi-Fi connection for the new device and connects to the server.

[1745] Step 26:

[1746] The server will transfer all existing data to the new device.

[1747] Step 27:

[1748] The device receives the migrated data and starts new support tailored to the growing user base.

[1749] Step 28:

[1750] The server analyzes the monitoring data from the new device and continues to provide consistent parenting support.

[1751] Step 29:

[1752] The device uses a camera and microphone to collect the user's facial expressions and tone of voice.

[1753] Step 30:

[1754] The data collected by the device is sent to the server in real time.

[1755] Step 31:

[1756] The server uses an emotion engine to analyze the collected data and recognize the user's emotional state.

[1757] Step 32:

[1758] The server adjusts the parenting advice based on the emotional data.

[1759] Step 33:

[1760] The server notifies the user of the adjusted advice.

[1761] Step 34:

[1762] The device displays a message via a smartphone app saying, "Your baby seems anxious. Please hold him."

[1763] Step 35:

[1764] The user sees the notification and takes the appropriate action.

[1765] Example 2

[1766] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1767] Modern childcare demands personalized services that meet the needs of children from newborn to adulthood. However, conventional systems have struggled to provide services while consistently transferring data and replacing devices appropriately as users grow. Recognizing users' emotions and providing appropriate advice is also a challenge. Furthermore, systems lacked the ability to quickly and automatically contact emergency personnel when an abnormality was detected.

[1768] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1769] In this invention, the server includes means for inputting basic information about the user, means for collecting data by monitoring the user's movements and voice, means for analyzing the collected data and providing advice to the user, means for making emergency contact when an abnormality is detected, means for transferring data to a subsequent device in accordance with the user's growth, an emotion engine for recognizing the user's emotions, and means for analyzing the emotion data recognized by the emotion engine and adjusting advice. This enables device replacement and data transfer in accordance with the user's growth, provision of personalized services based on emotions, and rapid emergency response.

[1770] The term "user" refers to a person who uses the system, and in the present invention refers to all users including newborns and their growing children.

[1771] The term "device" refers to all hardware devices used in the system of the present invention, including monitoring devices, recording devices, communication devices, and the like.

[1772] "Basic Information" refers to the default information about a User, including personally identifiable information such as name, date of birth, and gender.

[1773] "Means for monitoring movements and sounds" refers to the function of recording and collecting user actions and sounds in real time using input devices such as cameras and microphones.

[1774] "Data collection means" means any process or device that temporarily or permanently stores information such as a user's movements or voice.

[1775] "Means for analyzing data" refers to functions, including software and algorithms, that analyze collected data and identify specific patterns or trends.

[1776] "Means for providing advice" means a system function for making suggestions to users regarding childcare and health management based on the analysis results.

[1777] "Means for making emergency contact" refers to the function of promptly sending warnings or notifications to the user or designated third parties via communication means when an abnormality is detected.

[1778] "Means for transferring data" refers to the ability to transfer data from an old device to a new device as the user grows.

[1779] "Emotion-aware emotion engine" means specialized algorithms and software that analyze a user's facial expressions and tone of voice to recognize their emotional state.

[1780] "Means for analyzing emotional data and adjusting advice" refers to the function of appropriately adjusting the content of advice based on emotional data recognized by the emotion engine, thereby providing a more personalized service.

[1781] The system of the present invention aims to provide personalized services through device replacement, data transfer, and emotion recognition in accordance with the user's growth. This system is composed of multiple hardware and software components, the role of which is described in detail below.

[1782] Overall system configuration

[1783] The system consists of the following main components:

[1784] 1. A way to enter basic user information

[1785] 2. Collecting data by monitoring your movements and voice

[1786] 3. A means of analyzing collected data and providing advice to users

[1787] 4. Means of emergency contact when an abnormality is detected

[1788] 5. A way to transfer data to the next device as the user grows

[1789] 6. Emotion engine that recognizes user emotions

[1790] 7. Means for analyzing the emotional data recognized by the emotion engine and adjusting the advice

[1791] A means of entering basic user information

[1792] For initial setup, the user uses a smartphone application to enter basic information such as the user's name, date of birth, gender, etc. The device receives this information, sends it to the server, and stores it in a database. This information forms the basis for personalization in all subsequent processes.

[1793] A means of collecting data by monitoring user movements and voices

[1794] The device uses a camera and microphone to monitor the user's movements and voice 24 / 7, including movement patterns, tone of voice, facial expressions, etc. The collected data is sent to a server in real time.

[1795] A means of analyzing collected data and providing advice to users

[1796] The server analyzes the collected data and models the user's lifestyle and characteristics. Based on the analysis results, it generates specific advice for the user. For example, if the server recognizes that the user is feeling stressed, it will provide the advice "listen to music to relax." The device then notifies the user of this advice via a smartphone application.

[1797] A means of making emergency contact when an abnormality is detected

[1798] The device detects the user's abnormal movements or sounds. The server analyzes the abnormal data, determines that it is an emergency, and automatically sends an emergency notification to designated contacts (e.g., emergency contacts). The user receives the emergency notification through a smartphone application and can respond quickly.

[1799] A way to transfer data to the next device as the user grows

[1800] As a user grows, the server sends a migration notification to a device suitable for the next stage of growth. The user purchases a new device and performs initial setup. The device establishes the network settings for the new device and connects to the server. The server migrates all data to the new device and continues to provide consistent support.

[1801] Emotion engine that recognizes user emotions

[1802] The device uses a camera and voice recognition technology to analyze the user's facial expressions and tone of voice, and an emotion engine to recognize the user's emotions, allowing it to more accurately understand the user's needs and complaints.

[1803] A means of analyzing the emotional data recognized by the emotion engine and adjusting the advice

[1804] The server analyzes the emotion data collected by the emotion engine to assess the user's current emotional state. For example, if the server determines that the user is under stress, it provides special care advice. This advice is dynamically adjusted according to the user's emotional state, enabling more personalized care.

[1805] Processing explanation in natural language with concrete examples

[1806] For example, when a user enters basic information about a newborn into a smartphone app, the device sends this information to a server and stores it in a database. The device then uses a camera and microphone to monitor the baby's movements and sounds 24 / 7. The collected data is sent to the server in real time, which analyzes it. For example, if the server detects that the baby is crying frequently at night, it will notify the user through the smartphone app with advice to "play music at a regular rhythm." Furthermore, if the device detects abnormal movements or sounds from the baby, the server will determine this is an emergency and automatically contact emergency services. Finally, when the user turns two years old, the server will transfer the data to a new device, providing consistent childcare support.

[1807] Example prompts for generative AI models

[1808] "When a user uses a smartphone app to enter basic information about a newborn baby, please explain the specific processing steps of how that information is sent to the server and stored in the database."

[1809] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1810] Step 1:

[1811] The user launches a smartphone application and enters basic information about the newborn baby. The entered basic information includes the baby's name, date of birth, and gender. This information is collected within the application and sent to the device. The device converts this information into JSON format and sends it to the server using the HTTPS protocol. The server saves the received data in a database and returns a save completion response to the device.

[1812] Specific operation:

[1813] 1. The user opens the app's input form and enters the newborn's information.

[1814] 2. The device serializes the user input data into JSON.

[1815] 3. The device sends data to the server via HTTPS.

[1816] 4. The server validates the incoming data and saves it as a new record in the database.

[1817] 5. The server returns a save completion response to the terminal, and the terminal notifies the user.

[1818] Step 2:

[1819] The device monitors the user's movements and voice 24 / 7 using a camera and microphone. This monitoring captures the user's movement and voice patterns. This data is stored in a buffer at regular intervals and then securely transmitted to a server using a VPN.

[1820] Specific operation:

[1821] 1. The device begins capturing real-time data using the camera and microphone.

[1822] 2. Movement and audio data are temporarily stored in a buffer.

[1823] 3. At regular intervals, the contents of the buffer are sent to the server via VPN.

[1824] Step 3:

[1825] The server analyzes the received data and models the user's lifestyle and characteristics. The received data is processed by an analysis module to extract specific patterns and trends. This generates a user behavior model that is stored in a database.

[1826] Specific operation:

[1827] 1. The server passes the received data to a dedicated module that analyzes it.

[1828] 2. The analytics module runs algorithms that identify behavioral patterns and trends.

[1829] 3. Identified patterns and trends are modeled and stored in a database.

[1830] Step 4:

[1831] The server generates advice for the user based on the analysis results. The generated advice is notified to the user via a smartphone application. For example, if the server recognizes that the user is feeling stressed, it will provide the advice "listen to music to relax."

[1832] Specific operation:

[1833] 1. The server selects an advice template based on the analysis results.

[1834] 2. A specific message is generated based on the selected template.

[1835] 3. The generated advice is sent to the device, which then notifies the user via an app notification.

[1836] Step 5:

[1837] The device runs an algorithm to detect abnormal user movements or sounds. If an abnormality is detected, it sends an alert to the server. The server analyzes the alert data and, if an abnormality is detected, sends a notification to designated emergency contacts. The user receives the emergency notification through a smartphone application.

[1838] Specific operation:

[1839] 1. The device runs an anomaly detection algorithm that monitors real-time data.

[1840] 2. If an abnormality is detected, an alert is sent to the server immediately.

[1841] 3. The server analyzes the alert and, if it determines that there is an abnormality, sends a notification to the registered emergency contact.

[1842] 4. Users receive emergency notifications through the app and respond quickly.

[1843] Step 6:

[1844] The server sends migration notifications to new devices as users grow. The user purchases a new device and performs initial setup. The device establishes network settings for the new device and connects to the server. The server migrates all data to the new device and continues to provide consistent support.

[1845] Specific operation:

[1846] 1. The server monitors the user's growth data and generates migration notifications at appropriate times.

[1847] 2. The user purchases a new device and goes through the initial setup procedure.

[1848] 3. The device completes the network configuration of the new device and connects to the server.

[1849] 4. The server transfers the data from the old device to the new device.

[1850] Step 7:

[1851] The device uses a camera and voice recognition technology to analyze the user's facial expressions and tone of voice, and recognizes the user's emotions using an emotion engine. This data is sent to a server, which then analyzes it using the emotion engine. Based on the analysis results, tailored advice is provided to the user.

[1852] Specific operation:

[1853] 1. The device uses a camera and microphone to perform facial recognition and voice analysis.

[1854] 2. The analyzed data is sent to the server in real time.

[1855] 3. The server passes the data to the emotion engine to evaluate the user's emotional state.

[1856] 4. Based on the evaluation results, generate and notify tailored advice to the user.

[1857] (Application example 2)

[1858] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1859] While modern childcare demands personalized support tailored to each newborn's developmental stage, manual information management and decision-making are required, increasing the burden of childcare. It is also difficult to accurately grasp a newborn's emotional state and provide appropriate care based on that. Furthermore, childcare products and services are typically offered in brick-and-mortar stores, lacking personalization tailored to individual needs. This often results in inadequate childcare support.

[1860] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for inputting basic information about the newborn, a means for monitoring the newborn's movements and voice to collect data, a means for analyzing the collected data and providing advice to the user, a means for making an emergency call when an abnormality is detected, a means for recognizing the user's emotions and adjusting advice based on the emotion data, a means for transferring data to the next device as the user grows, and a means for proposing personalized products and services in physical stores and providing special care counseling. This enables seamless childcare support according to the newborn's growth stage, provision of appropriate care based on the newborn's emotional state, consistent data management, and provision of personalized services in physical stores according to individual needs.

[1861] "Means for inputting basic information about a newborn" is a function that allows a user to input basic information about a newborn, such as the name, date of birth, and gender, and send it to the server.

[1862] "Means for monitoring the movements and sounds of newborns and collecting data" refers to a function that uses cameras and microphones to monitor the movements and sounds of newborns 24 hours a day and collect data.

[1863] "Means for analyzing collected data and providing advice to users" refers to a function in which the server analyzes collected data, models the daily rhythms and characteristics of the newborn, and provides appropriate child-rearing advice to users.

[1864] "Means for making emergency contact when an abnormality is detected" is a function that allows the system to detect abnormal movements or sounds from the newborn and automatically notify emergency contacts.

[1865] "Means for recognizing the user's emotions and adjusting advice based on emotional data" refers to a function that uses an emotion engine to analyze the user's facial expressions and tone of voice and adjust advice to provide appropriate care.

[1866] "A way to transfer data to the next device as the user grows" is a feature that allows existing data to be transferred to a new device as the newborn grows, providing consistent parenting support.

[1867] "Means of proposing personalized products and services in physical stores and providing special care counseling" refers to a function that personalizes the proposal of childcare products and services in physical stores and provides care counseling according to individual needs.

[1868] The following system and its processing will be described as an embodiment of the present invention. This system provides optimized services by replacing devices according to the needs of a user as they grow from newborn, while inheriting personal data. Furthermore, it includes an emotion engine that recognizes the user's emotions and adjusts advice based on those emotions.

[1869] Overall system configuration

[1870] The system consists of the following main components:

[1871] 1. A way to enter basic information about newborns

[1872] 2. A means of collecting data by monitoring the movements and sounds of newborns

[1873] 3. A means of analyzing collected data and providing advice to users

[1874] 4. Means of emergency contact when an abnormality is detected

[1875] 5. A way to recognize user emotions and tailor recommendations based on emotional data

[1876] 6. A way to transfer data to the next device as users grow

[1877] 7. A way to offer personalized products and services in physical stores and provide special care counseling

[1878] A means of entering basic information about a newborn

[1879] For the initial setup, the user uses a smartphone app to enter basic information about the newborn, such as their name, date of birth, and gender. The device receives this information, sends it to a server, and stores it in a database. This information forms the basis for personalization in all subsequent processes.

[1880] A means of monitoring and collecting data on newborn movements and sounds

[1881] The device uses a camera and microphone to monitor the newborn's movements and sounds 24 / 7, including the baby's crying, sleep patterns, and body movements, and the collected data is sent to a server in real time.

[1882] A means of analyzing collected data and providing advice to users

[1883] The server analyzes the collected data and models the newborn's daily rhythm and characteristics. Based on the analysis results, it generates specific childcare advice for the user. For example, if a baby frequently cries at night, the server will provide the user with advice such as "play music at a steady rhythm." The device then notifies the user of this advice via a smartphone app.

[1884] A means of making emergency contact when an abnormality is detected

[1885] The device detects abnormal movements or sounds from the newborn. The server analyzes the abnormal data, determines whether it is an emergency, and automatically sends an emergency notification to designated contacts (e.g., ambulance, parents). The user receives the emergency notification through a smartphone app and can respond quickly.

[1886] A means of recognizing user emotions and tailoring advice based on emotional data

[1887] The device uses a camera and voice recognition technology to analyze the user's facial expressions and tone of voice, and recognizes the user's emotions using an emotion engine. This allows for more accurate understanding of the baby's needs and ailments. The server analyzes the emotion data collected by the emotion engine and evaluates the user's current emotional state. For example, if the server determines that the user is under stress, it will provide special care advice. This advice is dynamically adjusted according to the user's emotional state, enabling more personalized care.

[1888] A way to transfer data to the next device as users grow

[1889] When the user turns two years old, the server sends a notification to transition to a device suitable for the next stage of development. The user purchases a new device and sets it up. The device establishes the new device's Wi-Fi settings and connects to the server. The server transfers all personal data to the new device and continues to provide consistent support.

[1890] A means to offer personalized products and services in physical stores and provide special care counseling

[1891] There is a smartphone app that provides childcare products and services in brick-and-mortar stores, and the server proposes personalized products and services based on basic information about the newborn, their daily movements, and emotional data. The app also allows users to make reservations for care counseling sessions in brick-and-mortar stores and receive consultations in real time.

[1892] Specific examples

[1893] For example, when a user enters basic information about a newborn baby into a smartphone app, the device sends this information to a server and stores it in a database. The device then uses a camera and microphone to monitor the baby's movements and sounds 24 hours a day. The collected data is sent in real time to the server, which analyzes it. For example, if the server detects that the baby is crying frequently at night, it will notify the user through the smartphone app with advice to "play music at a regular rhythm."

[1894] By introducing the emotion engine, it becomes possible to more accurately grasp the baby's emotional state and provide appropriate care. For example, if the server recognizes that the baby is feeling strong anxiety in a particular situation, it will provide special advice to the user to provide a sense of security. In this way, the emotion engine realizes optimal support according to the user's emotions.

[1895] Example prompts for generative AI models

[1896] Generate the best advice for your crying baby based on the following data:

[1897] Basic information: Name "Newborn A", Date of birth "2022-01-01", Gender "Male"

[1898] Movement and sound data: "Frequent crying at night"

[1899] Emotion data: "crying face" and "anxious voice"

[1900] Output formats:

[1901] Advice: New Instructions

[1902] Additional Care Suggestions: Special Care Suggestions

[1903] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1904] Step 1:

[1905] The user enters basic information about the newborn into a smartphone app.

[1906] How it works: The user uses the app's input form to enter the newborn's name, date of birth, and gender, and the information is sent by the device to the server and stored in a database.

[1907] Input: Newborn's name, date of birth, sex

[1908] Output: Basic information of the newborn stored in the database

[1909] Step 2:

[1910] The device uses a camera and microphone to monitor the newborn's movements and sounds and collect data.

[1911] How it works: The device periodically activates the camera and microphone to monitor the newborn's movements and cries, and the collected data is sent to the server in real time.

[1912] Input: Video and audio data from the camera and microphone

[1913] Output: Monitoring data of the newborn's movements and voices sent to a server

[1914] Step 3:

[1915] The server analyzes the collected data and models the newborn's daily rhythms and characteristics.

[1916] How it works: The server analyzes the received data using machine learning algorithms to identify the time of day when the newborn is crying and their movement patterns.

[1917] Input: Neonatal movement and voice monitoring data

[1918] Output: Data modeling the daily rhythms and characteristics of newborns

[1919] Step 4:

[1920] The server generates parenting advice based on the analysis results and notifies the user via the device.

[1921] Specific operation: Based on the analysis data, the server creates parenting advice, such as "play music at a steady rhythm," and notifies the user via a smartphone app.

[1922] Input: Data modeling the daily rhythms and characteristics of newborns

[1923] Output: Parenting advice sent to a smartphone app

[1924] Step 5:

[1925] If the device detects any abnormal movements or sounds from the newborn, the server will automatically send an emergency notification.

[1926] Specific operation: When the device detects an abnormality, it sends the data to the server, which determines it is an emergency and automatically sends a notification to pre-defined emergency contacts.

[1927] Input: Unusual movement and audio data

[1928] Output:Notify emergency contacts

[1929] Step 6:

[1930] The device uses a camera and voice recognition technology to collect the user's emotional data, which is then analyzed by the server to tailor the advice.

[1931] How it works: The device uses a camera to capture the user's facial expressions and a microphone to analyze the tone of voice. The collected emotional data is sent to the server, which then adjusts the advice based on the user's emotional state.

[1932] Input: Emotion data from camera and microphone

[1933] Output: Advice based on emotional state

[1934] Step 7:

[1935] As the user grows, the server sends a notification for the next device migration and transfers the data to the new device.

[1936] What it does: When a user purchases and sets up a new device, the device establishes the device's Wi-Fi settings and connects to the server, which then transfers all personal data to the new device.

[1937] Input: New device setup information

[1938] Output: Personal data transferred to new device

[1939] Step 8:

[1940] Servers will suggest personalized products and services in physical stores and provide special care counseling.

[1941] How it works: The server recommends optimal products and services at physical stores based on the newborn's basic information, daily movements, and emotional data. The app also allows users to make appointments for special care counseling.

[1942] Input: Basic information of newborn baby, movement and voice data, emotion data

[1943] Output: Personalized recommendations and care counseling in physical stores

[1944] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1945] The data generation mod...

Claims

1. A system that provides services by replacing devices and transferring data according to the user's growth, A means of inputting basic information about the newborn; a means of monitoring and collecting data on the newborn's movements and sounds; A means of analyzing the collected data and providing advice to users; A means of making an emergency contact when an abnormality is detected; A system that includes a means to transfer data to the next device as the user grows.

2. The system of claim 1 further comprising means for pre-processing the collected data and modeling life rhythms and characteristics.

3. 10. The system of claim 1, further comprising means for automatically making emergency contact.

Images