System

Abstract

A system is provided.SOLUTION: An input unit configured to allow a parent to input sleep data of a baby, an analysis unit configured to receive and analyze the data input from the input unit, a schedule generation unit configured to generate an optimal sleep schedule according to the age in months and the growth stage of the baby based on the data analyzed by the analysis unit, a notification unit configured to notify the parent of the sleep schedule generated by the schedule generation unit, a schedule adjustment unit configured to correct and adjust the schedule based on new sleep data input by the parent, and a message generation unit configured to provide a psychological support message to the parent; A consultation reservation means for performing an individual consultation by an expert.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] Many parents are troubled by their babies' nighttime crying and fussiness, which can lead to sleep deprivation and stress for parents, becoming a major problem. There is also a lot of inconsistent information available online, making it difficult to know what to trust. Furthermore, it is difficult to find a sleep schedule that suits each family's lifestyle and the baby's developmental stage, making it difficult for both parents and babies to get quality sleep. A comprehensive solution to these issues is needed. [Means for solving the problem]

[0005] This invention provides a system that automatically generates and modifies an optimal sleep schedule based on the analysis of a parent's baby's sleep data, which is input by the parent. Specifically, the system includes an input means through which the parent inputs information such as the baby's sleep duration, wake-up time, nap times, and nighttime crying frequency. The system also includes an analysis means for analyzing the input data and a schedule generation means for generating an optimal sleep schedule based on the baby's age and developmental stage based on the analysis results. The system also includes a notification means for notifying the parent of the generated schedule, a schedule adjustment means for modifying and adjusting the schedule based on the new sleep data input by the parent, a message generation means for providing psychological support messages to the parent, and a consultation reservation means for individual consultations with a specialist. This system provides comprehensive support for the sleep environment of parents and babies, enabling them to achieve high-quality sleep.

[0006] "Input means" refers to the interface through which parents input their baby's sleep data.

[0007] "Analysis means" refers to a device or program for analyzing input sleep data and identifying the baby's sleep patterns.

[0008] "Schedule generation means" refers to a device or program that generates an optimal sleep schedule based on the baby's age and developmental stage based on the analyzed data.

[0009] "Notification means" refers to a system or device for notifying a parent of the generated sleep schedule.

[0010] "Schedule adjustment means" means a device or program that modifies or adjusts an existing sleep schedule based on new sleep data entered by a parent.

[0011] "Message generating means" refers to a device or program that automatically generates messages to provide psychological support messages to parents.

[0012] "Consultation booking means" refers to an interface or system that allows parents to book an individual consultation with a specialist.

[0013] "Generative artificial intelligence model" refers to a trained machine learning model used to analyze a baby's sleep patterns and suggest an optimal sleep schedule. [Brief explanation of the drawings]

[0014] [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

[0015] 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.

[0016] First, the terms used in the following description will be explained.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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."

[0022] [First embodiment]

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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."

[0035] This invention is a system that automatically generates and modifies an optimal sleep schedule based on the analysis of sleep data entered by parents. The purpose of this system is to provide comprehensive support for the sleep environment of parents and babies.

[0036] Program processing overview

[0037] Enter your baby's basic information and sleep data

[0038] User

[0039] Parents first enter their baby's basic information (name, age, gender, etc.) into the app, then enter their daily sleep data (wake-up time, bedtime, nap time, frequency of nighttime crying, etc.).

[0040] Terminal

[0041] The terminal transmits the input data to the server.

[0042] server

[0043] The server stores the received data in a database and analyzes it to identify the baby's sleep patterns.

[0044] Generation and presentation of optimal sleep schedule

[0045] server

[0046] The server then generates an optimal sleep schedule for the baby based on the baby's sleep patterns, including bedtime and daytime naps, and sends the schedule to the device.

[0047] Terminal

[0048] The device will then notify the parents of the generated sleep schedule, allowing them to get their baby to sleep based on this schedule.

[0049] Schedule adjustments

[0050] User

[0051] Parents will then re-enter any new sleep data their baby actually had, including whether they slept as planned and the actual hours of sleep.

[0052] Terminal

[0053] The terminal transmits the newly entered data to the server.

[0054] server

[0055] The server automatically adjusts the schedule based on the new data it receives, so that the next time it suggests a schedule that better suits your baby's sleep patterns.

[0056] Providing psychological support

[0057] server

[0058] To ease the psychological burden on parents, the server uses a generative AI model to automatically generate encouraging messages and advice. For example, the server might generate a message the day after a night of heavy crying, such as, "Today was tough, but it's part of growing up. You're a great mom."

[0059] Terminal

[0060] The device will then notify the parent of this automatically generated message, allowing the parent to receive psychological support.

[0061] Individual consultation with an expert

[0062] User

[0063] Parents can schedule a private consultation with a specialist within the app. For example, they can press the "Book a consultation" button and enter the desired date and time and the content of the consultation.

[0064] Terminal

[0065] The terminal transmits the reservation information to the server.

[0066] server

[0067] The server notifies the specialist of the reservation information and obtains confirmation.

[0068] Expert

[0069] Experts will interact with parents online at designated times and provide personalized advice.

[0070] Specific examples

[0071] Example 1: Initial Setup and Data Entry

[0072] User: Downloads and launches the app, then enters the baby's name as "Taro," age as "6 months," and gender as "male."

[0073] Terminal: Sends the entered information to the server.

[0074] Server: Receives information, stores it in a database, and begins initial analysis.

[0075] Example 2: Schedule Generation

[0076] User: Enter sleep data (e.g., went to bed at 7pm, cried twice at night, woke up at 6am, took one hour nap at 10am and one hour nap at 2pm).

[0077] Terminal: Sends entered data to the server.

[0078] Server: Analyzes the data using a generative AI model and generates the next schedule, suggesting "go to bed at 8pm, take 1 hour and 30 minute naps at 10am and 2pm."

[0079] Example 3: Providing psychological support messages

[0080] Server: After a series of nights of constant crying, the server automatically generates a message like, "Today was tough, but don't worry, it's part of growing up."

[0081] Device: Notifies parents of messages, giving them peace of mind.

[0082] This system allows parents to properly manage their baby's sleep and create an optimal sleeping environment with the help of expert advice. It also contributes to reducing stress for parents through psychological support. In this way, the present invention can improve the quality of sleep for both parents and babies.

[0083] The processing flow will be explained below.

[0084] Step 1:

[0085] User

[0086] Parents download the app and enter basic information about their baby (such as name, age, and gender) when they first launch it.

[0087] Step 2:

[0088] Terminal

[0089] The terminal transmits the input basic information to the server.

[0090] Step 3:

[0091] server

[0092] The server stores the received basic information about the baby in a database and prepares it for analysis.

[0093] Step 4:

[0094] User

[0095] Parents enter sleep data from the past 24 hours (wake-up time, bedtime, nap time, frequency of nighttime crying, etc.) into the app.

[0096] Step 5:

[0097] Terminal

[0098] The terminal transmits the input sleep data to the server.

[0099] Step 6:

[0100] server

[0101] The server analyzes the received sleep data to identify the baby's sleep patterns, which are then used to further analyze the data using a generative AI model.

[0102] Step 7:

[0103] server

[0104] The server uses a generative AI model to generate an optimal sleep schedule for the baby based on their age and developmental stage, including nighttime bedtime and daytime nap times.

[0105] Step 8:

[0106] server

[0107] The generated sleep schedule is sent to the device.

[0108] Step 9:

[0109] Terminal

[0110] The device will then notify the parent of the received sleep schedule, which the parent can then view on the app.

[0111] Step 10:

[0112] User

[0113] Parents can put their babies to sleep based on the schedule they are notified of.

[0114] Step 11:

[0115] User

[0116] Parents will then again enter the actual sleep performance for that day (e.g., whether they went to bed as planned, how long they slept, etc.) into the app.

[0117] Step 12:

[0118] Terminal

[0119] The terminal transmits the newly input sleep performance data to the server.

[0120] Step 13:

[0121] server

[0122] The server analyzes the new data and uses a generative AI model to optimize the schedule for the next day.

[0123] Step 14:

[0124] server

[0125] The new optimized schedule is sent to the device.

[0126] Step 15:

[0127] Terminal

[0128] The device will notify the parent of the new schedule and allow them to run it again.

[0129] Step 16:

[0130] server

[0131] The server uses a generative AI model to automatically generate messages aimed at providing psychological support to parents, including encouragement and advice.

[0132] Step 17:

[0133] server

[0134] Send the generated message to the terminal.

[0135] Step 18:

[0136] Terminal

[0137] The device will notify the parent of the message, who can then view it.

[0138] Step 19:

[0139] User

[0140] Parents select the option within the app to schedule a private consultation with a specialist, inputting the desired date and time and the details of the consultation.

[0141] Step 20:

[0142] Terminal

[0143] The terminal transmits the reservation information to the server.

[0144] Step 21:

[0145] server

[0146] The server notifies the specialist of the reservation information and obtains confirmation.

[0147] Step 22:

[0148] Expert

[0149] Experts will interact with parents online at designated times and provide personalized advice.

[0150] Step 23:

[0151] User

[0152] Parents can consult with an expert through the app at a designated time and receive necessary advice.

[0153] These steps guide the system through a series of processes to improve the baby's sleep quality and reduce stress for parents.

[0154] Example 1

[0155] 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."

[0156] Babies' sleep patterns vary greatly from baby to baby, making it extremely difficult for parents to establish an appropriate sleep schedule. As a result, parents often spend a lot of time and effort managing their baby's sleep, and become stressed. Furthermore, to receive specialized advice tailored to the baby's developmental stage, individual consultations with specialists are required, which is also time-consuming. Traditional methods make it difficult to comprehensively resolve these issues.

[0157] 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.

[0158] In this invention, the server includes an input means for a parent to input their baby's sleep data, an analysis means for receiving and analyzing the data input from the input means, a schedule generation means for generating an optimal sleep schedule based on the baby's age and developmental stage based on the data analyzed by the analysis means, a notification means for notifying the parent of the sleep schedule generated by the schedule generation means, a schedule adjustment means for modifying or adjusting the schedule based on the new sleep data input by the parent, a message generation means for providing psychological support messages to the parent, a consultation reservation means for individual consultations with a specialist, a transmission means for transmitting the data input from the input means to the server, a storage means for the server to store the baby's sleep data in a database, and a means for the analysis means to analyze the sleep patterns using a generative artificial intelligence model. This allows parents to automatically generate or modify an optimal sleep schedule based on their baby's individual sleep patterns and support their baby's development through psychological support messages and individual consultations with a specialist.

[0159] 1. "Input means" refers to a device or interface that allows parents to input their baby's sleep data.

[0160] 2. "Analysis means" refers to the device or algorithm used to analyze the input data and identify the baby's sleep patterns.

[0161] 3. "Schedule generation means" refers to a device or algorithm that creates an optimal sleep schedule based on the baby's age and developmental stage based on analyzed data.

[0162] 4. "Notification means" refers to a device or system that notifies parents of the generated sleep schedule.

[0163] 5. "Schedule Adjustment Tool" means a device or algorithm that modifies or adjusts a sleep schedule based on new sleep data entered by a parent.

[0164] 6. "Message generation means" refers to a device or system for generating and providing psychological support messages to parents.

[0165] 7. "Consultation booking means" refers to a device or system for booking an individual consultation with a specialist.

[0166] 8. "Transmission means" refers to a device or system for transmitting data entered through the input means to the server.

[0167] 9. "Storage means" refers to the device or system that allows the server to store the baby's sleep data in a database.

[0168] 10. "Generative AI model" refers to a machine learning algorithm that analyzes input data to understand and predict a baby's sleep patterns.

[0169] The present invention is a system that allows parents to input their baby's sleep data, analyzes the data, and automatically generates and modifies an optimal sleep schedule. The purpose of this system is to provide comprehensive support for the sleep environment of parents and babies. The following describes an embodiment of this system.

[0170] Enter your baby's basic information and sleep data

[0171] User

[0172] Parents use a smartphone app to enter basic information about their baby (such as name, age in months, and gender). The user then uses the app's input form to enter data, providing information such as the baby's name as "Taro," its age as "6 months," and its gender as "male." The parent then enters daily sleep data (such as wake-up time, bedtime, nap time, and frequency of nighttime crying) in the same way.

[0173] Sending input data

[0174] Terminal

[0175] The terminal organizes the data entered by the user and sends it to the server using a secure communication protocol (e.g. HTTPS). All entered data is encrypted and securely transferred to the server.

[0176] Data storage and analysis

[0177] server

[0178] The server stores the received user data in a database (e.g., MySQL). The stored data is indexed and organized for efficient search and analysis. The server then uses data analysis software, such as Python scripts, to analyze the sleep data and identify the baby's sleep patterns. Generative artificial intelligence models (generative AI models) are used in the analysis to improve the accuracy of data processing.

[0179] Generating an optimal sleep schedule

[0180] server

[0181] The server generates an optimal sleep schedule based on the identified baby's sleep patterns and developmental stage. A generative AI model (e.g., a model using TensorFlow) is used for generation. The model receives a prompt: "Please suggest a new sleep schedule based on the current sleep patterns of a 6-month-old baby." The server generates a new schedule as a prediction.

[0182] Schedule Notifications

[0183] Terminal

[0184] The device then notifies the parent of the optimal sleep schedule received from the server. The schedule is displayed on the parent's smartphone using the push notification function. For example, a specific schedule such as "Go to bed at 8 p.m., take 1.5 hour naps at 10 a.m. and 2 p.m." may be displayed.

[0185] Entering new sleep data

[0186] User

[0187] Parents then enter their baby's new sleep data into the app again, using a dedicated form in the app to record the actual number of hours of sleep, the number of nighttime crying episodes, and the length of naps in detail.

[0188] Rescheduling

[0189] Terminal

[0190] The device then sends the newly entered sleep data to the server, again via a secure communications protocol.

[0191] server

[0192] The server re-analyzes the current sleep schedule based on the new data received and automatically adjusts the schedule as needed, using machine learning algorithms to update the schedule based on the baby's latest sleep patterns.

[0193] Generating psychological support messages

[0194] server

[0195] The server automatically generates an encouraging message using a generative AI model (e.g., GPT-3) to provide psychological support to parents. An example of a prompt is "Please create an encouraging message for a parent whose child is crying a lot at night.", and generates an encouraging message for the parent.

[0196] Message notifications

[0197] Terminal

[0198] The device will then notify the parent of the generated encouraging message via an in-app message box or push notification, so the parent can see it immediately.

[0199] Book a private consultation with an expert

[0200] User

[0201] Parents press the "Book a consultation" button in the app and enter the desired date and time and the content of the consultation.

[0202] Terminal

[0203] The terminal transmits the reservation information input by the user to the server.

[0204] server

[0205] The server notifies the relevant specialist of the received reservation information, and the specialist prepares to interact with the parent online at the specified time and provide individual advice.

[0206] In this way, the present invention can provide a concrete means for improving the quality of sleep for parents and their babies, allowing parents to effectively manage their babies' sleep and reduce stress.

[0207] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0208] Step 1:

[0209] User

[0210] Parents launch the smartphone app and enter basic information about their baby (such as name, age in months, and gender). The data is entered in the format of "baby's name," "age in months," and "gender." Based on this, the app stores the information entered in the fields in an internal data structure.

[0211] Input: Baby's basic information (e.g. name, age, sex)

[0212] Output: Basic information stored in the app's internal data structures

[0213] Step 2:

[0214] Terminal

[0215] The terminal organizes the data entered by the user and sends it to the server using a secure communication protocol (e.g., HTTPS). The data for each field is serialized in JSON format or similar and sent to the server in encrypted form.

[0216] Input: Basic baby information

[0217] Output: Basic information sent to the server

[0218] Step 3:

[0219] server

[0220] The server stores the received user data in a database (e.g., MySQL), which is then indexed using a database management system and prepared for efficient later searching and analysis.

[0221] Input: Baby data sent from the device

[0222] Output: Baby data stored in a database

[0223] Step 4:

[0224] User

[0225] Parents enter daily sleep data (wake-up time, bedtime, nap time, nighttime crying frequency, etc.) into the app. As data is entered into input fields, the app stores it in an internal data structure.

[0226] Input: Sleep data (e.g., wake-up time, bedtime, nap time, frequency of night crying)

[0227] Output: Sleep data stored in the app's internal data structure

[0228] Step 5:

[0229] Terminal

[0230] The device organizes the sleep data entered by the user and sends it to the server using a secure communication protocol (e.g., HTTPS). The data is serialized in JSON format, encrypted, and sent to the server.

[0231] Input: Sleep data

[0232] Output: Sleep data sent to the server

[0233] Step 6:

[0234] server

[0235] The server stores the received sleep data in a database. It also analyzes the sleep data using analysis software such as Python scripts. A generative AI model is used for the analysis to identify the baby's sleep patterns. For example, the prompt sentence is "Based on the baby's sleep data, please identify the sleep patterns."

[0236] Input: Sleep data

[0237] Data processing / calculation: Analysis using generative AI models

[0238] Output: Identified sleep patterns

[0239] Step 7:

[0240] server

[0241] The server uses a generative AI model to generate an optimal sleep schedule based on the identified sleep patterns and age. The server generates a new schedule using the prompt, "Please suggest a new sleep schedule based on the current sleep patterns of a 6-month-old baby."

[0242] Input: Identified sleep pattern, age in months

[0243] Data processing / calculation: Schedule generation using generative AI models

[0244] Output: Optimal sleep schedule

[0245] Step 8:

[0246] Terminal

[0247] The device notifies the user of the optimal sleep schedule received from the server, and the schedule is displayed on the parent's smartphone using the push notification function.

[0248] Enter: your optimal sleep schedule.

[0249] Output: Sleep schedule notified to parent

[0250] Step 9:

[0251] User

[0252] The parent re-enters the new sleep data into the app, which updates the app's internal data structures.

[0253] Input: New sleep data

[0254] Output: New sleep data stored in the app's internal data structure.

[0255] Step 10:

[0256] Terminal

[0257] The device then sends the newly entered data to the server, again via a secure communications protocol.

[0258] Input: New sleep data

[0259] Output: New sleep data sent to the server.

[0260] Step 11:

[0261] server

[0262] The server reanalyzes the current schedule based on the new data received and automatically adjusts the schedule. Machine learning algorithms are used to update the optimal schedule based on the new data.

[0263] Input: New sleep data

[0264] Data processing / calculation: Reanalysis using machine learning algorithms

[0265] Output: Adjusted schedule

[0266] Step 12:

[0267] server

[0268] The server automatically generates encouraging messages using a generative AI model to provide psychological support to parents. The message is generated based on the prompt, "Please create an encouraging message for parents whose child has been crying a lot at night."

[0269] Input: Sleep data, generative AI model

[0270] Data processing / calculation: Message generation using generative AI models

[0271] Output: An encouraging message

[0272] Step 13:

[0273] Terminal

[0274] The device will then notify the parent of the generated encouraging message via a message box within the app or a push notification.

[0275] Input: An encouraging message

[0276] Output: Message sent to parent

[0277] Step 14:

[0278] User

[0279] Parents press the "Book a consultation" button in the app and enter the desired date and time and the content of the consultation.

[0280] Input: Reservation information (desired date and time, consultation details)

[0281] Output: Reservation information stored in the app's internal data structure

[0282] Step 15:

[0283] Terminal

[0284] The terminal transmits the reservation information input by the user to the server.

[0285] Input: Reservation information

[0286] Output: Reservation information sent to the server

[0287] Step 16:

[0288] server

[0289] The server notifies the relevant specialist of the received reservation information and prepares the specialist to interact with the parent online at the specified time.

[0290] Input: Reservation information

[0291] Output: Booking information notified to the expert

[0292] In this way, all the steps work together to form a system that provides a holistic supportive sleep environment for parents and babies.

[0293] (Application example 1)

[0294] 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."

[0295] As autonomous vehicle technology evolves, driver health and sleep management are becoming important issues for accident prevention and safe driving. Drivers driving long distances in particular need to be able to take appropriate breaks and receive immediate warnings when they feel drowsy. However, conventional systems often cannot meet these needs, so there is a need for technology that can accurately grasp the driver's health and psychological burden, and generate and notify optimal break schedules based on that information.

[0296] 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.

[0297] In this invention, the server includes input means for the driver to input sleep data, analysis means for receiving and analyzing the data input from the input means, schedule generation means for generating an optimal rest schedule according to the driver's health state based on the data analyzed by the analysis means, notification means for notifying the driver of the rest schedule generated by the schedule generation means, schedule adjustment means for correcting and adjusting the schedule based on the new sleep data input by the driver, message generation means for providing the driver with a psychological support message, and consultation reservation means for individual consultation with a specialist. This makes it possible to accurately grasp the driver's health state and psychological burden, and to generate and notify the optimal rest schedule and issue immediate warnings based on that information.

[0298] "Driver" means a person who uses or controls an automated vehicle.

[0299] "Sleep data" refers to information entered by the driver, such as the amount of sleep, wake-up time, rest time, and frequency of drowsiness.

[0300] "Input means" means a device or interface through which a driver inputs sleep data.

[0301] The "analysis means" refers to software or hardware for analyzing the sleep data received from the input means.

[0302] The "schedule generation means" is a system that creates an optimal rest schedule according to the driver's health condition based on the data analyzed by the analysis means.

[0303] The "notification means" refers to a device or interface for notifying the driver of the generated rest schedule.

[0304] The "schedule adjustment tool" refers to a system that modifies and adjusts existing schedules based on newly entered sleep data by drivers.

[0305] The "message generating means" refers to a system that generates psychological support messages for the driver.

[0306] A "consultation reservation means" is a device or interface that accepts reservations for individual consultations with experts.

[0307] A "generative AI model" is an artificial intelligence algorithm or system for analyzing data and generating messages.

[0308] This invention is a system for supporting the health and sleep management of drivers of self-driving vehicles, and is realized by the following steps.

[0309] System Overview

[0310] 1. Enter your sleep data

[0311] User: First, the driver installs the app and enters basic information (name, age, gender, etc.), then enters daily sleep data (wake-up time, bedtime, rest time, frequency of drowsiness, etc.).

[0312] Device: Use a device such as a smartphone or head-mounted display to send the input data to the server.

[0313] Server: The server stores the received data in a database (e.g., MySQL).

[0314] 2. Data analysis and schedule generation

[0315] Server: The server uses a generative AI model (such as TensorFlow) to analyze the stored data. The analytical model identifies the driver's health and sleep patterns.

[0316] Server: Based on the analysis results, the schedule generation means generates an optimal break schedule, which includes break timing and recommended break duration.

[0317] 3. Schedule notification and adjustment

[0318] Terminal: The generated rest schedule is communicated to the driver via smart glasses or a head-mounted display.

[0319] User: The driver re-enters new sleep data (e.g., unplanned nap, actual rest time, etc.).

[0320] Terminal: New data entered is sent to the server.

[0321] Server: Based on the new data, the schedule generator automatically adjusts the schedule and applies it next time, providing a more accurate break schedule.

[0322] 4. Real-time warning system

[0323] Server: The analysis means determines the driver's drowsiness in real time.

[0324] Device: When the driver feels drowsy, a warning message is displayed on smart glasses or a head-mounted display.

[0325] 5. Providing psychological support messages

[0326] Server: The server uses a generative AI model to automatically generate encouraging and advice messages, such as "You had a hard time today, but this is part of your growth. You're a great driver."

[0327] Device: This message is sent to the driver via smart glasses or a head-mounted display, allowing the driver to receive psychological support.

[0328] 6. Individual consultation with an expert

[0329] User: Drivers can schedule a private consultation with a sleep specialist within the app by pressing the "Book a Consultation" button and entering the desired date and time and the details of the consultation.

[0330] Terminal: The reservation information is sent to the server.

[0331] Server: The server notifies the expert of the reservation information and gets confirmation.

[0332] Experts: Experts will interact with drivers online at designated times and provide personalized advice.

[0333] Specific examples

[0334] Example prompt sentence:

[0335] User: Enter the driver's name, age, gender, and daily sleep data.

[0336] System: The proposed break time is 14:00. Please take a one-hour break now.

[0337] System: You are feeling drowsy. We recommend you take a break or seek professional advice.

[0338] System: You've had a tough day, but good luck. You're a great driver.

[0339] This system allows drivers to properly manage their health and receive expert advice to create an optimal rest environment. It also helps reduce driver stress through psychological support. This will improve the safety of autonomous vehicles and reduce the risk of accidents.

[0340] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0341] Step 1:

[0342] User: The driver installs the app and enters basic information (name, age, gender, etc.) Once this basic information is entered, the device sends it to the server.

[0343] Input: Driver's name, age, gender

[0344] Output: Send basic information to the server

[0345] Step 2:

[0346] Device: The driver enters their daily sleep data (wake-up time, bedtime, rest time, frequency of drowsiness, etc.) into the app. The device then sends this data to the server.

[0347] Input: Driver sleep duration, wake-up time, rest time, frequency of drowsiness

[0348] Output: Send sleep data to the server

[0349] Step 3:

[0350] Server: The server stores the received basic information and daily sleep data in a database (e.g., MySQL). The stored data is analyzed using a generative AI model (e.g., TensorFlow).

[0351] Input: Basic information and sleep data to the server

[0352] Output: Data storage in database, data analysis using analytical model

[0353] Step 4:

[0354] Server: Based on the data analyzed using the generative AI model, the driver's health condition and sleep patterns are identified. Based on the analysis results, the server generates an optimal rest schedule using a schedule generation tool.

[0355] Input: Analyzed sleep data

[0356] Output: Generate an optimal break schedule

[0357] Step 5:

[0358] Terminal: The generated rest schedule is notified to the driver via smart glasses or a head-mounted display. The schedule information is displayed in real time using the notification method.

[0359] Input: Break schedule from schedule generator

[0360] Output: Notify driver of break schedule

[0361] Step 6:

[0362] User: The driver enters new sleep data (e.g., unplanned naps, actual rest times, etc.) into the device. The device sends the new data to the server.

[0363] Input: New sleep data

[0364] Output: Send new data to the server

[0365] Step 7:

[0366] Server: Based on the new sleep data, the server recalculates and adjusts the existing rest schedule using the schedule adjustment method.

[0367] Input: New sleep data

[0368] Output: Generate an adjusted break schedule

[0369] Step 8:

[0370] Device: The adjusted break schedule is notified to the driver, and the device displays the adjusted schedule in real time.

[0371] Input: Adjusted break schedule

[0372] Output: Notification of adjusted schedule to driver

[0373] Step 9:

[0374] Server: The analysis means determines the driver's drowsiness in real time. If drowsiness is detected, the server immediately generates a warning message.

[0375] Input: Real-time driver status data

[0376] Output: Generate a warning message

[0377] Step 10:

[0378] Device: When a driver feels drowsy, a warning message will appear on the smart glasses or head-mounted display, prompting them to take an immediate break.

[0379] Input: warning message

[0380] Output: Notify driver of warning message

[0381] Step 11:

[0382] Server: The server uses a generative AI model to automatically generate encouraging and advice messages, such as "You had a hard time today, but this is part of your growth. You're a great driver."

[0383] Input: Driver sleep and health data

[0384] Output: Generates encouraging and advice messages

[0385] Step 12:

[0386] Device: The generated psychological support message is sent to the driver via smart glasses or a head-mounted display.

[0387] Input: Support message

[0388] Output: Notify driver of support message

[0389] Step 13:

[0390] Users: Drivers can book a private consultation with a sleep specialist within the app by entering the desired date and time and the details of the consultation.

[0391] Input: Consultation reservation information

[0392] Output: Send reservation information to the server

[0393] Step 14:

[0394] Server: The reservation information is stored on the server and notified to the expert. An online dialogue with the expert is prepared.

[0395] Input: Consultation reservation data

[0396] Output: Expert notification and confirmation

[0397] Step 15:

[0398] Experts: Experts will interact with drivers online at designated times and provide personalized advice.

[0399] Input: Consultation details from the driver, reservation information

[0400] Output: Expert advice

[0401] 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.

[0402] This system combines a system that allows parents to input their baby's sleep data, analyzes it, and generates and modifies an optimal sleep schedule, with an emotion engine that recognizes the user's emotions. The system aims to provide comprehensive support for the sleep environment of parents and babies, and reduce the psychological burden on parents.

[0403] Program processing overview

[0404] Enter your baby's basic information and sleep data

[0405] User

[0406] Parents first enter their baby's basic information (name, age, gender, etc.) into the app, then enter their daily sleep data (wake-up time, bedtime, nap time, frequency of nighttime crying, etc.).

[0407] Terminal

[0408] The terminal transmits the input data to the server.

[0409] server

[0410] The server stores the received data in a database and analyzes the information, which can then be used to identify the baby's sleep patterns.

[0411] Generation and presentation of optimal sleep schedule

[0412] server

[0413] The server uses the generative AI model to generate an optimal sleep schedule for the baby based on their age and developmental stage, including bedtime and daytime naps, and then sends the schedule to the device.

[0414] Terminal

[0415] The device will then notify the parents of the generated sleep schedule, allowing them to get their baby to sleep based on this schedule.

[0416] Schedule adjustments

[0417] User

[0418] Parents will then re-enter any new sleep data their baby actually had, including whether they slept as planned and the actual hours of sleep.

[0419] Terminal

[0420] The terminal transmits the newly entered data to the server.

[0421] server

[0422] The server automatically adjusts the schedule based on the new data, so that the next time it suggests a schedule that better suits your baby's sleep patterns.

[0423] Providing psychological support

[0424] server

[0425] The server uses a generative AI model to automatically generate encouragement and advice that is sensitive to the parent's feelings. For example, the day after a night of heavy crying, the server might generate a message like, "Today was tough, but this is part of growing up. You're a great mom."

[0426] Terminal

[0427] The device will then notify the parent of this automatically generated message, allowing the parent to receive psychological support.

[0428] Individual consultation with an expert

[0429] User

[0430] Parents select the option to book a private consultation with a specialist within the app and enter the desired date and time and the details of the consultation.

[0431] Terminal

[0432] The terminal transmits the reservation information to the server.

[0433] server

[0434] The server notifies the specialist of the reservation information and obtains confirmation.

[0435] Expert

[0436] Experts will interact with parents online at designated times and provide personalized advice.

[0437] Recognizing user emotions with an emotion engine

[0438] Terminal

[0439] The text and voice data that parents enter into the app, as well as biometric information (such as heart rate and facial expressions), are sent to the emotion engine.

[0440] server

[0441] The server's emotion engine analyzes this data to determine the parent's emotional state, whether they are stressed, relieved, or experiencing a specific emotion.

[0442] Emotion-based message generation

[0443] server

[0444] Based on the analysis results of the emotion engine, the generative AI model generates a message that best suits that emotion. For example, if a parent is tired, it will generate a message such as, "Thank you for your hard work today. It's important to take a short rest."

[0445] Terminal

[0446] The generated message is sent to the device and notified to the parent, allowing the parent to receive support appropriate to the child's emotions at that time.

[0447] Specific examples

[0448] Example 1: Initial Setup and Data Entry

[0449] User: Downloads and launches the app, then enters the baby's name as "Taro," age as "6 months," and gender as "male."

[0450] Terminal: Sends the entered information to the server.

[0451] Server: Receives information, stores it in a database, and begins initial analysis.

[0452] Example 2: Schedule Generation

[0453] User: Enter sleep data (e.g., went to bed at 7pm, cried twice at night, woke up at 6am, took one hour nap at 10am and one hour nap at 2pm).

[0454] Terminal: Sends entered data to the server.

[0455] Server: Analyzes the data using a generative AI model and generates the next schedule, suggesting "go to bed at 8pm, take 1 hour and 30 minute naps at 10am and 2pm."

[0456] Example 3: Psychological support through an emotional engine

[0457] User: Texts "I'm so tired because my baby is crying at night."

[0458] Terminal: Sends the entered text data to the emotion engine on the server.

[0459] Server: The emotion engine analyzes the text and identifies that the parent is tired. The generative AI model generates a message such as, "Today was tough. It's important to take some rest."

[0460] Device: Notify parent of message.

[0461] This allows the system to not only optimize the baby's sleep schedule, but also provide support tailored to the parent's psychological state through an emotion engine, reducing stress for the parent.

[0462] The processing flow will be explained below.

[0463] Step 1:

[0464] User

[0465] Parents download the app and enter basic information about their baby (such as name, age, and gender) when they first launch it.

[0466] Step 2:

[0467] Terminal

[0468] The terminal transmits the input basic information to the server.

[0469] Step 3:

[0470] server

[0471] The server stores the received basic information about the baby in a database and prepares it for analysis.

[0472] Step 4:

[0473] User

[0474] Parents enter their child's daily sleep data (wake-up time, bedtime, nap time, frequency of nighttime crying, etc.) into the app.

[0475] Step 5:

[0476] Terminal

[0477] The device transmits the entered sleep data to the server.

[0478] Step 6:

[0479] server

[0480] The server analyzes the received sleep data and identifies the baby's sleep patterns.

[0481] Step 7:

[0482] server

[0483] Based on the analyzed data, the generative AI model generates an optimal sleep schedule based on the baby's age and developmental stage.

[0484] Step 8:

[0485] server

[0486] The generated sleep schedule is sent to the device.

[0487] Step 9:

[0488] Terminal

[0489] The device notifies the parent of the generated sleep schedule.

[0490] Step 10:

[0491] User

[0492] Parents can put their babies to sleep based on the schedule they are notified of.

[0493] Step 11:

[0494] User

[0495] Enter your actual sleep performance for that day (e.g., whether you slept as planned, how long you slept, etc.) into the app again.

[0496] Step 12:

[0497] Terminal

[0498] The terminal transmits the newly input sleep performance data to the server.

[0499] Step 13:

[0500] server

[0501] The server analyzes the new data and a generative AI model optimizes the schedule for the next day.

[0502] Step 14:

[0503] server

[0504] The optimized schedule is sent to the device again.

[0505] Step 15:

[0506] Terminal

[0507] The device will notify parents of the new schedule.

[0508] Step 16:

[0509] User

[0510] Parents input text and voice information about their daily situations and stresses into the app, and biometric information (e.g., heart rate, facial expressions, etc.) is automatically sent to the emotion engine.

[0511] Step 17:

[0512] Terminal

[0513] The device transmits the input text, voice, and biometric information to the server.

[0514] Step 18:

[0515] server

[0516] The server uses an emotion engine to analyze the parent's emotional state from the received data, determining whether the parent is stressed or relieved, for example.

[0517] Step 19:

[0518] server

[0519] Based on the results of the emotion engine, the generative AI model generates a message that best matches the parent's emotions. For example, if the parent is tired, it generates a message such as, "Thank you for your hard work today. It's important to take a short rest."

[0520] Step 20:

[0521] server

[0522] Send the generated message to the terminal.

[0523] Step 21:

[0524] Terminal

[0525] The device notifies the parent of the message, who then views the message.

[0526] Step 22:

[0527] User

[0528] Parents can schedule a private consultation with a specialist using the options within the app, inputting the desired date and time and the content of the consultation.

[0529] Step 23:

[0530] Terminal

[0531] The terminal transmits the reservation information to the server.

[0532] Step 24:

[0533] server

[0534] The server notifies the specialist of the reservation information and obtains confirmation.

[0535] Step 25:

[0536] Expert

[0537] Experts will interact with parents online at designated times and provide personalized advice.

[0538] Step 26:

[0539] User

[0540] Parents can consult with an expert through the app at a designated time and receive necessary advice.

[0541] This means that AI Nentore not only manages babies' sleep, but also provides psychological support to parents, making it a comprehensive sleep support system.

[0542] Example 2

[0543] 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."

[0544] In today's world, it is extremely difficult for parents to properly manage their baby's sleep and maintain an optimal sleep schedule. New parents, in particular, often experience stress due to a lack of knowledge about their baby's sleep patterns, which prevents them from responding appropriately. Furthermore, parents often ignore their own emotional state, which increases parenting stress. Another problem is the lack of easy access to individual consultations with specialists.

[0545] 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.

[0546] In this invention, the server includes input means for parents to input their baby's sleep data, analysis means for receiving and analyzing the data input from the input means, and schedule generation means for generating an optimal sleep schedule for the baby based on the data analyzed by the analysis means, according to the baby's age and developmental stage. This allows parents to appropriately manage their baby's sleep status and maintain an optimal sleep schedule.

[0547] The "input means" is an interface that allows parents to input their baby's sleep data and basic information.

[0548] The "analysis means" is a system for analyzing the data received from the input means and identifying the baby's sleep patterns.

[0549] The "schedule generation means" is a system for generating an optimal sleep schedule according to the baby's age and developmental stage based on the data obtained by the analysis means.

[0550] The "notification means" is a system for notifying parents of the generated sleep schedule so that the parents can be aware of the schedule.

[0551] The "schedule adjustment tool" is a system for correcting and adjusting existing sleep schedules based on new sleep data entered by parents.

[0552] The "message generating means" is a system for providing psychological support messages to parents.

[0553] The "emotion engine means" is a system for analyzing input text, voice, and biometric information to identify the parent's emotional state.

[0554] The "emotion message generating means" is a system for generating an appropriate message based on the parent's emotional state identified by the emotion engine means.

[0555] The "consultation reservation means" is a system that allows parents to make reservations for individual consultations with specialists.

[0556] This invention is a comprehensive childcare support system that combines a system that analyzes and generates an optimal sleep schedule based on the input of a parent's baby's sleep data, with an emotion engine that recognizes the user's emotions. This system aims to not only optimize a baby's sleep environment, but also to reduce the psychological burden on parents.

[0557] Enter your baby's basic information and sleep data

[0558] User

[0559] Parents first enter their baby's basic information (name, age, gender, etc.) into the app, then enter their daily sleep data (wake-up time, bedtime, nap time, frequency of nighttime crying, etc.).

[0560] Terminal

[0561] The terminal transmits the input data to the server. For example, a device equipped with a user interface, such as a smartphone or tablet, is used.

[0562] server

[0563] The server stores the received data in a database (e.g., MySQL, PostgreSQL, etc.). The stored data undergoes initial analysis using analytical tools. For example, analytical software such as Python or R can be used.

[0564] Generation and presentation of optimal sleep schedule

[0565] server

[0566] The server uses a generative AI model (e.g., OpenAI GPT-3) based on the analyzed data to generate an optimal sleep schedule for the baby based on their age and developmental stage. This schedule includes bedtime and nap times. The generated schedule is then sent to the device.

[0567] Terminal

[0568] The device will notify parents of the generated sleep schedule via a pop-up message or alert.

[0569] Schedule adjustments

[0570] User

[0571] Parents re-enter new sleep data, including whether the sleep plan was met and the actual sleep duration.

[0572] Terminal

[0573] The terminal transmits the newly entered data to the server.

[0574] server

[0575] The server will automatically adjust the schedule based on the new data, and the next suggested schedule will be revised to something like "Go to bed at 8 PM, take 1.5 hour naps at 10 AM and 2 PM."

[0576] Providing psychological support

[0577] server

[0578] The server uses a generative AI model to automatically generate encouragement and advice that is sensitive to the parent's feelings. For example, the day after a night of heavy crying, it might generate a message like, "Today was tough, but this is part of growing up. You're a great mom."

[0579] Terminal

[0580] The device notifies the parent of this automatically generated message.

[0581] Individual consultation with an expert

[0582] User

[0583] Within the app, parents select the option to book a private consultation with a specialist and enter the desired date and time and the details of the consultation.

[0584] Terminal

[0585] The terminal transmits the reservation information to the server.

[0586] server

[0587] The server notifies the specialist of the reservation information and obtains confirmation.

[0588] Expert

[0589] Experts will interact with parents online at designated times and provide personalized advice.

[0590] Recognizing user emotions with an emotion engine

[0591] Terminal

[0592] The text, voice data, and even biometric information (e.g., heart rate, facial expressions, etc.) that parents enter into the app are sent to the emotion engine.

[0593] server

[0594] The server's emotion engine analyzes this data and identifies the parent's emotional state, for example, by analyzing emotions such as "stress" or "fatigue" from the text data.

[0595] Emotion-based message generation

[0596] server

[0597] Based on the analysis results of the emotion engine, the generative AI model generates a message appropriate to that emotion. For example, if a parent is tired, it might generate a message such as, "Thank you for your hard work today. It's important to take a short rest."

[0598] Terminal

[0599] The generated message is sent to the device and notified to the parent, allowing the parent to receive support appropriate to the child's emotions at that time.

[0600] Specific examples

[0601] Example 1: Initial Setup and Data Entry

[0602] User: Downloads and launches the app, then enters the baby's name as "Taro," its age as "6 months," and its gender as "male."

[0603] Terminal: Sends the entered information to the server.

[0604] Server: Receives the information, stores it in a database, and begins initial analysis.

[0605] Example 2: Schedule Generation

[0606] User: Enter sleep data (e.g., went to bed at 7pm, cried twice at night, woke up at 6am, took one hour nap at 10am and one hour nap at 2pm).

[0607] Terminal: Sends the entered data to the server.

[0608] Server: Analyzes the data using a generative AI model and generates the next schedule, suggesting "Go to bed at 8pm, take 1 hour and 30 minute naps at 10am and 2pm."

[0609] Example 3: Psychological support through an emotional engine

[0610] User: Texts "I'm so tired because my baby is crying at night."

[0611] Terminal: Sends the entered text data to the emotion engine on the server.

[0612] Server: The emotion engine analyzes the text and identifies that the parent is tired. The generative AI model generates a message such as, "Today was tough. It's important to take some rest."

[0613] Device: Notify parent of message.

[0614] The system will be able to optimize a baby's sleep schedule and provide support tailored to the parent's psychological state through an emotion engine.

[0615] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0616] Step 1:

[0617] User

[0618] Parents download and install the app, then launch it and enter basic information about their baby (such as name, age, and gender), and then enter their baby's daily sleep data (for example, wake-up time, bedtime, nap time, and frequency of nighttime crying).

[0619] Terminal

[0620] The device sends the basic information and sleep data of the baby entered by the parent to the server in real time.

[0621] server

[0622] The server stores the received data in a database, which can be a database management system such as MySQL or PostgreSQL, and then prepares the data for initial analysis.

[0623] Step 2:

[0624] server

[0625] The server analyzes the stored data using an analytical tool, which may be data analysis software such as Python or R. The results of the analysis identify the baby's basic sleep patterns.

[0626] Input: Parent-entered baby information and sleep data

[0627] Output: Analysis of baby's sleep patterns

[0628] Step 3:

[0629] server

[0630] Based on the analysis results, the server uses a generative AI model (e.g., OpenAI GPT-3) to generate an optimal sleep schedule based on the baby's age and developmental stage, including bedtime and nap times.

[0631] Input: Analysis of baby's sleep patterns

[0632] Output: Optimal sleep schedule

[0633] Next, this generated schedule is transmitted to the terminal.

[0634] Step 4:

[0635] Terminal

[0636] The device will notify parents of the optimal sleep schedule sent from the server via pop-up messages and alerts.

[0637] User

[0638] Parents can check the notifications and use the generated sleep schedule to put their baby to bed or adjust nap times.

[0639] Enter: your optimal sleep schedule.

[0640] Output: Parental sleep schedule enforcement

[0641] Step 5:

[0642] User

[0643] Parents then enter the new sleep data into the app again, including details about whether the child was able to sleep as planned and the actual hours of sleep.

[0644] Terminal

[0645] The device sends new sleep data to the server, also in real time.

[0646] Input: New sleep data

[0647] Output: Send new sleep data

[0648] Step 6:

[0649] server

[0650] The server reanalyzes the schedule based on the newly sent sleep data and automatically adjusts it, generating and suggesting a more optimal sleep pattern for the next time.

[0651] Input: New sleep data

[0652] Output: Corrected sleep schedule

[0653] Step 7:

[0654] server

[0655] The server uses an emotion engine to understand the parent's feelings. The parent inputs text, voice data, and biometric information (e.g., heart rate, facial expression, etc.), and based on this, the parent's emotional state is identified.

[0656] Input: text, voice data, biometric information

[0657] Output: Parent's emotional state

[0658] Step 8:

[0659] server

[0660] Based on the parent's emotional state identified by the emotion engine, the generative AI model generates an appropriate message of encouragement or advice, such as, "Today was tough. It's important to take some rest."

[0661] Input: Parent emotional state

[0662] Output: An appropriate message of encouragement or advice

[0663] Step 9:

[0664] Terminal

[0665] The device will notify the parent of the generated message via a push notification or a pop-up message.

[0666] Input: A suitable message of encouragement or advice

[0667] Output: Message notification to parent

[0668] Step 10:

[0669] User

[0670] Parents can use the in-app options to schedule a private consultation with a specialist, inputting the desired topic, date and time.

[0671] Terminal

[0672] The terminal transmits the input reservation information to the server.

[0673] Input: Reservation information (consultation details, date and time)

[0674] Output: Send reservation information

[0675] Step 11:

[0676] server

[0677] The server forwards the received reservation information to the specialist and obtains confirmation of the reservation.

[0678] Input: Reservation information

[0679] Output: Coordination and confirmation with experts

[0680] Step 12:

[0681] Expert

[0682] The expert will then speak to the parent online at a confirmed date and time to provide personalized advice.

[0683] Input: Consultation received from parent

[0684] Output: Personalized advice from an expert

[0685] Through these steps, the system optimizes the baby's sleep schedule, provides support tailored to the parent's psychological state through an emotion engine, and offers expert consultations for more specific advice.

[0686] (Application example 2)

[0687] 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."

[0688] Conventional baby sleep management systems are limited to collecting and analyzing baby sleep data, and lack elements to reduce the psychological burden on parents. Furthermore, they do not provide support that takes into account the parents' emotional and stress states, making it difficult for them to maintain their mental stability. Therefore, there is a need for a more comprehensive support system that can also respond to parents' emotional states.

[0689] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0690] In this invention, the server includes input means for a parent to input sleep data of the child, analysis means for receiving and analyzing the data input from the input means, schedule generation means for generating an optimal sleep schedule according to the child's age and developmental stage based on the data analyzed by the analysis means, notification means for notifying the parent of the sleep schedule generated by the schedule generation means, schedule adjustment means for modifying or adjusting the schedule based on the new sleep data input by the parent, message generation means for providing psychological support messages to the parent, emotion analysis means for receiving and analyzing emotional data of the parent, emotion-based message generation means for generating appropriate support messages for the parent based on the emotional data analyzed by the emotion analysis means, and consultation reservation means for individual consultation with a specialist. This enables not only the optimization of the baby's sleep schedule but also support according to the parent's psychological state.

[0691] The "input means" is an interface that allows parents to input their child's sleep data and emotional state.

[0692] The "analysis means" is a means having a function of analyzing data received from the input means.

[0693] The "schedule generating means" is a means for generating an optimal sleep schedule according to the child's age and stage of development based on the data analyzed by the analyzing means.

[0694] The "notification means" is a means for notifying parents of the generated sleep schedule.

[0695] The "schedule adjustment tool" is a tool for correcting and adjusting the schedule based on new sleep data entered by the parent.

[0696] The "message generating means" is a means for providing psychological support messages to parents.

[0697] The "emotion analysis means" is a means for receiving the parent's emotion data and analyzing the parent's emotional state.

[0698] The "emotion-based message generating means" is a means for generating an appropriate support message for the parent based on the emotion data analyzed by the emotion analyzing means.

[0699] The "consultation reservation means" is a means for making a reservation for individual consultation with a specialist.

[0700] A "generative artificial intelligence model" is a machine learning model that generates optimal schedules and messages based on input data.

[0701] The present invention provides a system that analyzes a child's sleep data entered by a parent and generates and modifies an optimal sleep schedule, as well as a system that recognizes the parent's emotions and provides support messages in response to those emotions. Specific embodiments for implementing this system are described below.

[0702] Hardware and Software

[0703] Hardware:

[0704] Smartphone: Used by parents to enter data and receive notifications from the system.

[0705] Server: The central component responsible for receiving and analyzing data, generating sleep schedules, and sentiment analysis.

[0706] software:

[0707] Python 3.x: Used to implement system-wide programs.

[0708] GUI library (Tkinter): Used to build a user interface for the parent to input data.

[0709] Machine learning libraries: Used to perform data analysis, schedule generation, and emotion recognition using generative AI models.

[0710] System configuration

[0711] 1. Input method:

[0712] Parents use their smartphones to input information such as their child's sleep time, wake-up time, nap time, frequency of night crying, and emotional state into a user interface.

[0713] 2. Analysis method:

[0714] The server analyzes the data received from the input means to identify the child's sleep patterns, using a generative AI model for highly accurate analysis.

[0715] 3. Schedule generation method:

[0716] The server generates an optimal sleep schedule based on the child's age and developmental stage using a generative AI model, and the generated schedule is sent to the smartphone.

[0717] 4. Means of notification:

[0718] The generated sleep schedule is sent to parents' smartphones, helping them put their children to bed at realistic times.

[0719] 5. Scheduling methods:

[0720] When parents enter new sleep data, the server automatically adjusts the schedule based on that data and provides the optimal schedule again.

[0721] 6. Message Generation Method:

[0722] The server uses the generative AI model to provide parents with psychological support messages, such as "Today was tough, but it's part of growing up. You're a great mom" the day after a night of heavy crying.

[0723] 7. Emotion analysis means:

[0724] The system analyzes parental input, including text, voice, and biometric information (heart rate, facial expressions, etc.) to identify the child's emotional state. Emotion analysis is also performed using a generative AI model.

[0725] 8. Emotion-based message generation method:

[0726] Based on the results of emotion analysis, a support message is generated. For example, if the system detects that a parent is "tired," it generates a message such as "Thank you for your hard work today. It's important to take a short rest."

[0727] 9. How to book a consultation:

[0728] It provides a user interface for parents to book individual consultations with specialists. The booking information is sent to the server and confirmed and approved by the specialist.

[0729] Specific examples

[0730] Example 1: Initial Setup and Data Entry

[0731] The parent downloads and launches the app, entering the child's name as "Taro," age as "6 months," and gender as "male."

[0732] The smartphone sends the entered information to the server, which stores the received information in a database and begins initial analysis.

[0733] Example 2: Schedule Generation

[0734] Parents enter sleep data (e.g., baby goes to bed at 7pm, cries twice at night, wakes up at 6am, takes one-hour naps at 10am and 2pm).

[0735] The smartphone sends the input data to the server, which then analyzes it using a generative AI model to generate the next schedule.

[0736] The generated schedule suggests "go to bed at 8pm, take 1 hour and 30 minute naps at 10am and 2pm."

[0737] Example 3: Psychological support through an emotional engine

[0738] A parent texts, "I'm so tired because my baby is crying at night."

[0739] The smartphone sends the entered text data to the server's emotion engine, which analyzes the text and determines that the parent is tired.

[0740] The generative AI model generates messages such as, "Today was tough. It's important to take some rest."

[0741] A message is sent to the smartphone, and parents can receive psychological support.

[0742] Example prompt sentence:

[0743] Please enter your baby's basic information. Name: "Taro", Age: "6 months", Gender: Do not enter

[0744] Next, enter your baby's sleep data: Wake-up time: "06:00", Bedtime: "20:00", Nap time: "2 times, 1 hour each", Night crying: "2 times"

[0745] Enter your emotion. Emotion: "I'm tired."

[0746] In this manner, the present invention can optimize the baby's sleep schedule as well as provide support according to the parent's emotional state, thereby comprehensively supporting the sleep environment for both parent and baby.

[0747] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0748] Step 1:

[0749] Parents enter basic information about their children.

[0750] How it works: The user (parent) uses the smartphone's user interface to enter basic information about their child, such as their name, age, and gender.

[0751] Input: Name, age, gender

[0752] Output: Basic information data

[0753] Data processing: The basic information entered is sent from the smartphone to the server.

[0754] Step 2:

[0755] An initial analysis is performed based on basic information.

[0756] Operation: The server stores the received basic information in a database and begins initial analysis. Based on the analysis results, it prepares for initial configuration.

[0757] Input: Basic information data

[0758] Output: Analysis result data

[0759] Data calculation: Analyze basic information and generate basic analysis results according to the child's age.

[0760] Step 3:

[0761] Parents enter their child's sleep data.

[0762] Operation: The user (parent) uses the smartphone's user interface to input their child's sleep data (e.g., wake-up time, bedtime, nap time, frequency of night crying, etc.).

[0763] Input: Sleep data (wake-up time, bedtime, nap time, frequency of night crying)

[0764] Output: Sleep data

[0765] Data processing: The entered sleep data is sent from the smartphone to the server.

[0766] Step 4:

[0767] Analyzes sleep data and generates an optimal sleep schedule.

[0768] How it works: The server analyzes the input sleep data using a generative AI model and generates an optimal sleep schedule based on the child's age and developmental stage.

[0769] Input: Sleep data

[0770] Output: Optimal sleep schedule

[0771] Data Computing: Generative AI models are used to analyze data and generate schedules.

[0772] Step 5:

[0773] The generated sleep schedule is notified to the parent.

[0774] How it works: The server notifies the smartphone of the generated optimal sleep schedule, and the user (parent) receives the notification.

[0775] Enter: optimal sleep schedule

[0776] Output: Notification message

[0777] Data processing: The generated schedule is processed into a notification message and sent to the smartphone.

[0778] Step 6:

[0779] Parents enter new sleep data and reschedule.

[0780] How it works: The user (parent) re-enters sleep data, and the server automatically readjusts the schedule based on that data.

[0781] Input: New sleep data

[0782] Output: A recalibrated optimal sleep schedule

[0783] Data calculations: Recalculate the schedule based on new data using generative AI models.

[0784] Step 7:

[0785] Parental emotional data is input and the emotional state is analyzed.

[0786] Operation: The user (parent) inputs emotional data (text, voice, biometric information, etc.) using the smartphone's user interface. The server analyzes the emotional data using emotion analysis means and identifies the parent's emotional state.

[0787] Input: Emotion data

[0788] Output: Emotion analysis results

[0789] Data processing: The emotional data is analyzed using emotion analysis means to identify the emotional state of the parents.

[0790] Step 8:

[0791] A support message based on the results of emotion analysis is generated and notified to the parent.

[0792] How it works: Based on the results of emotion analysis, the server uses a generative AI model to generate an appropriate support message for the parent. The generated message is then sent to the smartphone.

[0793] Input: Sentiment analysis results

[0794] Output: Support message

[0795] Data calculation: Based on the results of sentiment analysis, a generative AI model generates support messages.

[0796] Step 9:

[0797] Book a private consultation with an expert.

[0798] Operation: The user (parent) makes an appointment with a specialist using the user interface on their smartphone. The appointment information is sent to the server and notified to the specialist.

[0799] Input: Reservation information (desired date and time, consultation details, etc.)

[0800] Output: Reservation confirmation message

[0801] Data processing: The reservation information is sent to the server and notified to the specialist.

[0802] 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.

[0803] 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.

[0804] 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.

[0805] [Second embodiment]

[0806] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0807] 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.

[0808] 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).

[0809] 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.

[0810] 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.

[0811] 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).

[0812] 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.

[0813] 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.

[0814] 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.

[0815] 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.

[0816] 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.

[0817] 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."

[0818] This invention is a system that automatically generates and modifies an optimal sleep schedule based on the analysis of sleep data entered by parents. The purpose of this system is to provide comprehensive support for the sleep environment of parents and babies.

[0819] Program processing overview

[0820] Enter your baby's basic information and sleep data

[0821] User

[0822] Parents first enter their baby's basic information (name, age, gender, etc.) into the app, then enter their daily sleep data (wake-up time, bedtime, nap time, frequency of nighttime crying, etc.).

[0823] Terminal

[0824] The terminal transmits the input data to the server.

[0825] server

[0826] The server stores the received data in a database and analyzes it to identify the baby's sleep patterns.

[0827] Generation and presentation of optimal sleep schedule

[0828] server

[0829] The server then generates an optimal sleep schedule for the baby based on the baby's sleep patterns, including bedtime and daytime naps, and sends the schedule to the device.

[0830] Terminal

[0831] The device will then notify the parents of the generated sleep schedule, allowing them to get their baby to sleep based on this schedule.

[0832] Schedule adjustments

[0833] User

[0834] Parents will then re-enter any new sleep data their baby actually had, including whether they slept as planned and the actual hours of sleep.

[0835] Terminal

[0836] The terminal transmits the newly entered data to the server.

[0837] server

[0838] The server automatically adjusts the schedule based on the new data it receives, so that the next time it suggests a schedule that better suits your baby's sleep patterns.

[0839] Providing psychological support

[0840] server

[0841] To ease the psychological burden on parents, the server uses a generative AI model to automatically generate encouraging messages and advice. For example, the server might generate a message the day after a night of heavy crying, such as, "Today was tough, but it's part of growing up. You're a great mom."

[0842] Terminal

[0843] The device will then notify the parent of this automatically generated message, allowing the parent to receive psychological support.

[0844] Individual consultation with an expert

[0845] User

[0846] Parents can schedule a private consultation with a specialist within the app. For example, they can press the "Book a consultation" button and enter the desired date and time and the content of the consultation.

[0847] Terminal

[0848] The terminal transmits the reservation information to the server.

[0849] server

[0850] The server notifies the specialist of the reservation information and obtains confirmation.

[0851] Expert

[0852] Experts will interact with parents online at designated times and provide personalized advice.

[0853] Specific examples

[0854] Example 1: Initial Setup and Data Entry

[0855] User: Downloads and launches the app, then enters the baby's name as "Taro," age as "6 months," and gender as "male."

[0856] Terminal: Sends the entered information to the server.

[0857] Server: Receives information, stores it in a database, and begins initial analysis.

[0858] Example 2: Schedule Generation

[0859] User: Enter sleep data (e.g., went to bed at 7pm, cried twice at night, woke up at 6am, took one hour nap at 10am and one hour nap at 2pm).

[0860] Terminal: Sends entered data to the server.

[0861] Server: Analyzes the data using a generative AI model and generates the next schedule, suggesting "go to bed at 8pm, take 1 hour and 30 minute naps at 10am and 2pm."

[0862] Example 3: Providing psychological support messages

[0863] Server: After a series of nights of constant crying, the server automatically generates a message like, "Today was tough, but don't worry, it's part of growing up."

[0864] Device: Notifies parents of messages, giving them peace of mind.

[0865] This system allows parents to properly manage their baby's sleep and create an optimal sleeping environment with the help of expert advice. It also contributes to reducing stress for parents through psychological support. In this way, the present invention can improve the quality of sleep for both parents and babies.

[0866] The processing flow will be explained below.

[0867] Step 1:

[0868] User

[0869] Parents download the app and enter basic information about their baby (such as name, age, and gender) when they first launch it.

[0870] Step 2:

[0871] Terminal

[0872] The terminal transmits the input basic information to the server.

[0873] Step 3:

[0874] server

[0875] The server stores the received basic information about the baby in a database and prepares it for analysis.

[0876] Step 4:

[0877] User

[0878] Parents enter sleep data from the past 24 hours (wake-up time, bedtime, nap time, frequency of nighttime crying, etc.) into the app.

[0879] Step 5:

[0880] Terminal

[0881] The terminal transmits the input sleep data to the server.

[0882] Step 6:

[0883] server

[0884] The server analyzes the received sleep data to identify the baby's sleep patterns, which are then used to further analyze the data using a generative AI model.

[0885] Step 7:

[0886] server

[0887] The server uses a generative AI model to generate an optimal sleep schedule for the baby based on their age and developmental stage, including nighttime bedtime and daytime nap times.

[0888] Step 8:

[0889] server

[0890] The generated sleep schedule is sent to the device.

[0891] Step 9:

[0892] Terminal

[0893] The device will then notify the parent of the received sleep schedule, which the parent can then view on the app.

[0894] Step 10:

[0895] User

[0896] Parents can put their babies to sleep based on the schedule they are notified of.

[0897] Step 11:

[0898] User

[0899] Parents will then again enter the actual sleep performance for that day (e.g., whether they went to bed as planned, how long they slept, etc.) into the app.

[0900] Step 12:

[0901] Terminal

[0902] The terminal transmits the newly input sleep performance data to the server.

[0903] Step 13:

[0904] server

[0905] The server analyzes the new data and uses a generative AI model to optimize the schedule for the next day.

[0906] Step 14:

[0907] server

[0908] The new optimized schedule is sent to the device.

[0909] Step 15:

[0910] Terminal

[0911] The device will notify the parent of the new schedule and allow them to run it again.

[0912] Step 16:

[0913] server

[0914] The server uses a generative AI model to automatically generate messages aimed at providing psychological support to parents, including encouragement and advice.

[0915] Step 17:

[0916] server

[0917] Send the generated message to the terminal.

[0918] Step 18:

[0919] Terminal

[0920] The device will notify the parent of the message, who can then view it.

[0921] Step 19:

[0922] User

[0923] Parents select the option within the app to schedule a private consultation with a specialist, inputting the desired date and time and the details of the consultation.

[0924] Step 20:

[0925] Terminal

[0926] The terminal transmits the reservation information to the server.

[0927] Step 21:

[0928] server

[0929] The server notifies the specialist of the reservation information and obtains confirmation.

[0930] Step 22:

[0931] Expert

[0932] Experts will interact with parents online at designated times and provide personalized advice.

[0933] Step 23:

[0934] User

[0935] Parents can consult with an expert through the app at a designated time and receive necessary advice.

[0936] These steps guide the system through a series of processes to improve the baby's sleep quality and reduce stress for parents.

[0937] Example 1

[0938] 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."

[0939] Babies' sleep patterns vary greatly from baby to baby, making it extremely difficult for parents to establish an appropriate sleep schedule. As a result, parents often spend a lot of time and effort managing their baby's sleep, and become stressed. Furthermore, to receive specialized advice tailored to the baby's developmental stage, individual consultations with specialists are required, which is also time-consuming. Traditional methods make it difficult to comprehensively resolve these issues.

[0940] 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.

[0941] In this invention, the server includes an input means for a parent to input their baby's sleep data, an analysis means for receiving and analyzing the data input from the input means, a schedule generation means for generating an optimal sleep schedule based on the baby's age and developmental stage based on the data analyzed by the analysis means, a notification means for notifying the parent of the sleep schedule generated by the schedule generation means, a schedule adjustment means for modifying or adjusting the schedule based on the new sleep data input by the parent, a message generation means for providing psychological support messages to the parent, a consultation reservation means for individual consultations with a specialist, a transmission means for transmitting the data input from the input means to the server, a storage means for the server to store the baby's sleep data in a database, and a means for the analysis means to analyze the sleep patterns using a generative artificial intelligence model. This allows parents to automatically generate or modify an optimal sleep schedule based on their baby's individual sleep patterns and support their baby's development through psychological support messages and individual consultations with a specialist.

[0942] 1. "Input means" refers to a device or interface that allows parents to input their baby's sleep data.

[0943] 2. "Analysis means" refers to the device or algorithm used to analyze the input data and identify the baby's sleep patterns.

[0944] 3. "Schedule generation means" refers to a device or algorithm that creates an optimal sleep schedule based on the baby's age and developmental stage based on analyzed data.

[0945] 4. "Notification means" refers to a device or system that notifies parents of the generated sleep schedule.

[0946] 5. "Schedule Adjustment Tool" means a device or algorithm that modifies or adjusts a sleep schedule based on new sleep data entered by a parent.

[0947] 6. "Message generation means" refers to a device or system for generating and providing psychological support messages to parents.

[0948] 7. "Consultation booking means" refers to a device or system for booking an individual consultation with a specialist.

[0949] 8. "Transmission means" refers to a device or system for transmitting data entered through the input means to the server.

[0950] 9. "Storage means" refers to the device or system that allows the server to store the baby's sleep data in a database.

[0951] 10. "Generative AI model" refers to a machine learning algorithm that analyzes input data to understand and predict a baby's sleep patterns.

[0952] The present invention is a system that allows parents to input their baby's sleep data, analyzes the data, and automatically generates and modifies an optimal sleep schedule. The purpose of this system is to provide comprehensive support for the sleep environment of parents and babies. The following describes an embodiment of this system.

[0953] Enter your baby's basic information and sleep data

[0954] User

[0955] Parents use a smartphone app to enter basic information about their baby (such as name, age in months, and gender). The user then uses the app's input form to enter data, providing information such as the baby's name as "Taro," its age as "6 months," and its gender as "male." The parent then enters daily sleep data (such as wake-up time, bedtime, nap time, and frequency of nighttime crying) in the same way.

[0956] Sending input data

[0957] Terminal

[0958] The terminal organizes the data entered by the user and sends it to the server using a secure communication protocol (e.g. HTTPS). All entered data is encrypted and securely transferred to the server.

[0959] Data storage and analysis

[0960] server

[0961] The server stores the received user data in a database (e.g., MySQL). The stored data is indexed and organized for efficient search and analysis. The server then uses data analysis software, such as Python scripts, to analyze the sleep data and identify the baby's sleep patterns. Generative artificial intelligence models (generative AI models) are used in the analysis to improve the accuracy of data processing.

[0962] Generating an optimal sleep schedule

[0963] server

[0964] The server generates an optimal sleep schedule based on the identified baby's sleep patterns and developmental stage. A generative AI model (e.g., a model using TensorFlow) is used for generation. The model receives a prompt: "Please suggest a new sleep schedule based on the current sleep patterns of a 6-month-old baby." The server generates a new schedule as a prediction.

[0965] Schedule Notifications

[0966] Terminal

[0967] The device then notifies the parent of the optimal sleep schedule received from the server. The schedule is displayed on the parent's smartphone using the push notification function. For example, a specific schedule such as "Go to bed at 8 p.m., take 1.5 hour naps at 10 a.m. and 2 p.m." may be displayed.

[0968] Entering new sleep data

[0969] User

[0970] Parents then enter their baby's new sleep data into the app again, using a dedicated form in the app to record the actual number of hours of sleep, the number of nighttime crying episodes, and the length of naps in detail.

[0971] Rescheduling

[0972] Terminal

[0973] The device then sends the newly entered sleep data to the server, again via a secure communications protocol.

[0974] server

[0975] The server re-analyzes the current sleep schedule based on the new data received and automatically adjusts the schedule as needed, using machine learning algorithms to update the schedule based on the baby's latest sleep patterns.

[0976] Generating psychological support messages

[0977] server

[0978] The server automatically generates an encouraging message using a generative AI model (e.g., GPT-3) to provide psychological support to parents. An example of a prompt is "Please create an encouraging message for a parent whose child is crying a lot at night.", and generates an encouraging message for the parent.

[0979] Message notifications

[0980] Terminal

[0981] The device will then notify the parent of the generated encouraging message via an in-app message box or push notification, so the parent can see it immediately.

[0982] Book a private consultation with an expert

[0983] User

[0984] Parents press the "Book a consultation" button in the app and enter the desired date and time and the content of the consultation.

[0985] Terminal

[0986] The terminal transmits the reservation information input by the user to the server.

[0987] server

[0988] The server notifies the relevant specialist of the received reservation information, and the specialist prepares to interact with the parent online at the specified time and provide individual advice.

[0989] In this way, the present invention can provide a concrete means for improving the quality of sleep for parents and their babies, allowing parents to effectively manage their babies' sleep and reduce stress.

[0990] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0991] Step 1:

[0992] User

[0993] Parents launch the smartphone app and enter basic information about their baby (such as name, age in months, and gender). The data is entered in the format of "baby's name," "age in months," and "gender." Based on this, the app stores the information entered in the fields in an internal data structure.

[0994] Input: Baby's basic information (e.g. name, age, sex)

[0995] Output: Basic information stored in the app's internal data structures

[0996] Step 2:

[0997] Terminal

[0998] The terminal organizes the data entered by the user and sends it to the server using a secure communication protocol (e.g., HTTPS). The data for each field is serialized in JSON format or similar and sent to the server in encrypted form.

[0999] Input: Basic baby information

[1000] Output: Basic information sent to the server

[1001] Step 3:

[1002] server

[1003] The server stores the received user data in a database (e.g., MySQL), which is then indexed using a database management system and prepared for efficient later searching and analysis.

[1004] Input: Baby data sent from the device

[1005] Output: Baby data stored in a database

[1006] Step 4:

[1007] User

[1008] Parents enter daily sleep data (wake-up time, bedtime, nap time, nighttime crying frequency, etc.) into the app. As data is entered into input fields, the app stores it in an internal data structure.

[1009] Input: Sleep data (e.g., wake-up time, bedtime, nap time, frequency of night crying)

[1010] Output: Sleep data stored in the app's internal data structure

[1011] Step 5:

[1012] Terminal

[1013] The device organizes the sleep data entered by the user and sends it to the server using a secure communication protocol (e.g., HTTPS). The data is serialized in JSON format, encrypted, and sent to the server.

[1014] Input: Sleep data

[1015] Output: Sleep data sent to the server

[1016] Step 6:

[1017] server

[1018] The server stores the received sleep data in a database. It also analyzes the sleep data using analysis software such as Python scripts. A generative AI model is used for the analysis to identify the baby's sleep patterns. For example, the prompt sentence is "Based on the baby's sleep data, please identify the sleep patterns."

[1019] Input: Sleep data

[1020] Data processing / calculation: Analysis using generative AI models

[1021] Output: Identified sleep patterns

[1022] Step 7:

[1023] server

[1024] The server uses a generative AI model to generate an optimal sleep schedule based on the identified sleep patterns and age. The server generates a new schedule using the prompt, "Please suggest a new sleep schedule based on the current sleep patterns of a 6-month-old baby."

[1025] Input: Identified sleep pattern, age in months

[1026] Data processing / calculation: Schedule generation using generative AI models

[1027] Output: Optimal sleep schedule

[1028] Step 8:

[1029] Terminal

[1030] The device notifies the user of the optimal sleep schedule received from the server, and the schedule is displayed on the parent's smartphone using the push notification function.

[1031] Enter: your optimal sleep schedule.

[1032] Output: Sleep schedule notified to parent

[1033] Step 9:

[1034] User

[1035] The parent re-enters the new sleep data into the app, which updates the app's internal data structures.

[1036] Input: New sleep data

[1037] Output: New sleep data stored in the app's internal data structure.

[1038] Step 10:

[1039] Terminal

[1040] The device then sends the newly entered data to the server, again via a secure communications protocol.

[1041] Input: New sleep data

[1042] Output: New sleep data sent to the server.

[1043] Step 11:

[1044] server

[1045] The server reanalyzes the current schedule based on the new data received and automatically adjusts the schedule. Machine learning algorithms are used to update the optimal schedule based on the new data.

[1046] Input: New sleep data

[1047] Data processing / calculation: Reanalysis using machine learning algorithms

[1048] Output: Adjusted schedule

[1049] Step 12:

[1050] server

[1051] The server automatically generates encouraging messages using a generative AI model to provide psychological support to parents. The message is generated based on the prompt, "Please create an encouraging message for parents whose child has been crying a lot at night."

[1052] Input: Sleep data, generative AI model

[1053] Data processing / calculation: Message generation using generative AI models

[1054] Output: An encouraging message

[1055] Step 13:

[1056] Terminal

[1057] The device will then notify the parent of the generated encouraging message via a message box within the app or a push notification.

[1058] Input: An encouraging message

[1059] Output: Message sent to parent

[1060] Step 14:

[1061] User

[1062] Parents press the "Book a consultation" button in the app and enter the desired date and time and the content of the consultation.

[1063] Input: Reservation information (desired date and time, consultation details)

[1064] Output: Reservation information stored in the app's internal data structure

[1065] Step 15:

[1066] Terminal

[1067] The terminal transmits the reservation information input by the user to the server.

[1068] Input: Reservation information

[1069] Output: Reservation information sent to the server

[1070] Step 16:

[1071] server

[1072] The server notifies the relevant specialist of the received reservation information and prepares the specialist to interact with the parent online at the specified time.

[1073] Input: Reservation information

[1074] Output: Booking information notified to the expert

[1075] In this way, all the steps work together to form a system that provides a holistic supportive sleep environment for parents and babies.

[1076] (Application example 1)

[1077] 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."

[1078] As autonomous vehicle technology evolves, driver health and sleep management are becoming important issues for accident prevention and safe driving. Drivers driving long distances in particular need to be able to take appropriate breaks and receive immediate warnings when they feel drowsy. However, conventional systems often cannot meet these needs, so there is a need for technology that can accurately grasp the driver's health and psychological burden, and generate and notify optimal break schedules based on that information.

[1079] 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.

[1080] In this invention, the server includes input means for the driver to input sleep data, analysis means for receiving and analyzing the data input from the input means, schedule generation means for generating an optimal rest schedule according to the driver's health state based on the data analyzed by the analysis means, notification means for notifying the driver of the rest schedule generated by the schedule generation means, schedule adjustment means for correcting and adjusting the schedule based on the new sleep data input by the driver, message generation means for providing the driver with a psychological support message, and consultation reservation means for individual consultation with a specialist. This makes it possible to accurately grasp the driver's health state and psychological burden, and to generate and notify the optimal rest schedule and issue immediate warnings based on that information.

[1081] "Driver" means a person who uses or controls an automated vehicle.

[1082] "Sleep data" refers to information entered by the driver, such as the amount of sleep, wake-up time, rest time, and frequency of drowsiness.

[1083] "Input means" means a device or interface through which a driver inputs sleep data.

[1084] The "analysis means" refers to software or hardware for analyzing the sleep data received from the input means.

[1085] The "schedule generation means" is a system that creates an optimal rest schedule according to the driver's health condition based on the data analyzed by the analysis means.

[1086] The "notification means" refers to a device or interface for notifying the driver of the generated rest schedule.

[1087] The "schedule adjustment tool" refers to a system that modifies and adjusts existing schedules based on newly entered sleep data by drivers.

[1088] The "message generating means" refers to a system that generates psychological support messages for the driver.

[1089] A "consultation reservation means" is a device or interface that accepts reservations for individual consultations with experts.

[1090] A "generative AI model" is an artificial intelligence algorithm or system for analyzing data and generating messages.

[1091] This invention is a system for supporting the health and sleep management of drivers of self-driving vehicles, and is realized by the following steps.

[1092] System Overview

[1093] 1. Enter your sleep data

[1094] User: First, the driver installs the app and enters basic information (name, age, gender, etc.), then enters daily sleep data (wake-up time, bedtime, rest time, frequency of drowsiness, etc.).

[1095] Device: Use a device such as a smartphone or head-mounted display to send the input data to the server.

[1096] Server: The server stores the received data in a database (e.g., MySQL).

[1097] 2. Data analysis and schedule generation

[1098] Server: The server uses a generative AI model (such as TensorFlow) to analyze the stored data. The analytical model identifies the driver's health and sleep patterns.

[1099] Server: Based on the analysis results, the schedule generation means generates an optimal break schedule, which includes break timing and recommended break duration.

[1100] 3. Schedule notification and adjustment

[1101] Terminal: The generated rest schedule is communicated to the driver via smart glasses or a head-mounted display.

[1102] User: The driver re-enters new sleep data (e.g., unplanned nap, actual rest time, etc.).

[1103] Terminal: New data entered is sent to the server.

[1104] Server: Based on the new data, the schedule generator automatically adjusts the schedule and applies it next time, providing a more accurate break schedule.

[1105] 4. Real-time warning system

[1106] Server: The analysis means determines the driver's drowsiness in real time.

[1107] Device: When the driver feels drowsy, a warning message is displayed on smart glasses or a head-mounted display.

[1108] 5. Providing psychological support messages

[1109] Server: The server uses a generative AI model to automatically generate encouraging and advice messages, such as "You had a hard time today, but this is part of your growth. You're a great driver."

[1110] Device: This message is sent to the driver via smart glasses or a head-mounted display, allowing the driver to receive psychological support.

[1111] 6. Individual consultation with an expert

[1112] User: Drivers can schedule a private consultation with a sleep specialist within the app by pressing the "Book a Consultation" button and entering the desired date and time and the details of the consultation.

[1113] Terminal: The reservation information is sent to the server.

[1114] Server: The server notifies the expert of the reservation information and gets confirmation.

[1115] Experts: Experts will interact with drivers online at designated times and provide personalized advice.

[1116] Specific examples

[1117] Example prompt sentence:

[1118] User: Enter the driver's name, age, gender, and daily sleep data.

[1119] System: The proposed break time is 14:00. Please take a one-hour break now.

[1120] System: You are feeling drowsy. We recommend you take a break or seek professional advice.

[1121] System: You've had a tough day, but good luck. You're a great driver.

[1122] This system allows drivers to properly manage their health and receive expert advice to create an optimal rest environment. It also helps reduce driver stress through psychological support. This will improve the safety of autonomous vehicles and reduce the risk of accidents.

[1123] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1124] Step 1:

[1125] User: The driver installs the app and enters basic information (name, age, gender, etc.) Once this basic information is entered, the device sends it to the server.

[1126] Input: Driver's name, age, gender

[1127] Output: Send basic information to the server

[1128] Step 2:

[1129] Device: The driver enters their daily sleep data (wake-up time, bedtime, rest time, frequency of drowsiness, etc.) into the app. The device then sends this data to the server.

[1130] Input: Driver sleep duration, wake-up time, rest time, frequency of drowsiness

[1131] Output: Send sleep data to the server

[1132] Step 3:

[1133] Server: The server stores the received basic information and daily sleep data in a database (e.g., MySQL). The stored data is analyzed using a generative AI model (e.g., TensorFlow).

[1134] Input: Basic information and sleep data to the server

[1135] Output: Data storage in database, data analysis using analytical model

[1136] Step 4:

[1137] Server: Based on the data analyzed using the generative AI model, the driver's health condition and sleep patterns are identified. Based on the analysis results, the server generates an optimal rest schedule using a schedule generation tool.

[1138] Input: Analyzed sleep data

[1139] Output: Generate an optimal break schedule

[1140] Step 5:

[1141] Terminal: The generated rest schedule is notified to the driver via smart glasses or a head-mounted display. The schedule information is displayed in real time using the notification method.

[1142] Input: Break schedule from schedule generator

[1143] Output: Notify driver of break schedule

[1144] Step 6:

[1145] User: The driver enters new sleep data (e.g., unplanned naps, actual rest times, etc.) into the device. The device sends the new data to the server.

[1146] Input: New sleep data

[1147] Output: Send new data to the server

[1148] Step 7:

[1149] Server: Based on the new sleep data, the server recalculates and adjusts the existing rest schedule using the schedule adjustment method.

[1150] Input: New sleep data

[1151] Output: Generate an adjusted break schedule

[1152] Step 8:

[1153] Device: The adjusted break schedule is notified to the driver, and the device displays the adjusted schedule in real time.

[1154] Input: Adjusted break schedule

[1155] Output: Notification of adjusted schedule to driver

[1156] Step 9:

[1157] Server: The analysis means determines the driver's drowsiness in real time. If drowsiness is detected, the server immediately generates a warning message.

[1158] Input: Real-time driver status data

[1159] Output: Generate a warning message

[1160] Step 10:

[1161] Device: When a driver feels drowsy, a warning message will appear on the smart glasses or head-mounted display, prompting them to take an immediate break.

[1162] Input: warning message

[1163] Output: Notify driver of warning message

[1164] Step 11:

[1165] Server: The server uses a generative AI model to automatically generate encouraging and advice messages, such as "You had a hard time today, but this is part of your growth. You're a great driver."

[1166] Input: Driver sleep and health data

[1167] Output: Generates encouraging and advice messages

[1168] Step 12:

[1169] Device: The generated psychological support message is sent to the driver via smart glasses or a head-mounted display.

[1170] Input: Support message

[1171] Output: Notify driver of support message

[1172] Step 13:

[1173] Users: Drivers can book a private consultation with a sleep specialist within the app by entering the desired date and time and the details of the consultation.

[1174] Input: Consultation reservation information

[1175] Output: Send reservation information to the server

[1176] Step 14:

[1177] Server: The reservation information is stored on the server and notified to the expert. An online dialogue with the expert is prepared.

[1178] Input: Consultation reservation data

[1179] Output: Expert notification and confirmation

[1180] Step 15:

[1181] Experts: Experts will interact with drivers online at designated times and provide personalized advice.

[1182] Input: Consultation details from the driver, reservation information

[1183] Output: Expert advice

[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] This system combines a system that allows parents to input their baby's sleep data, analyzes it, and generates and modifies an optimal sleep schedule, with an emotion engine that recognizes the user's emotions. The system aims to provide comprehensive support for the sleep environment of parents and babies, and reduce the psychological burden on parents.

[1186] Program processing overview

[1187] Enter your baby's basic information and sleep data

[1188] User

[1189] Parents first enter their baby's basic information (name, age, gender, etc.) into the app, then enter their daily sleep data (wake-up time, bedtime, nap time, frequency of nighttime crying, etc.).

[1190] Terminal

[1191] The terminal transmits the input data to the server.

[1192] server

[1193] The server stores the received data in a database and analyzes the information, which can then be used to identify the baby's sleep patterns.

[1194] Generation and presentation of optimal sleep schedule

[1195] server

[1196] The server uses the generative AI model to generate an optimal sleep schedule for the baby based on their age and developmental stage, including bedtime and daytime naps, and then sends the schedule to the device.

[1197] Terminal

[1198] The device will then notify the parents of the generated sleep schedule, allowing them to get their baby to sleep based on this schedule.

[1199] Schedule adjustments

[1200] User

[1201] Parents will then re-enter any new sleep data their baby actually had, including whether they slept as planned and the actual hours of sleep.

[1202] Terminal

[1203] The terminal transmits the newly entered data to the server.

[1204] server

[1205] The server automatically adjusts the schedule based on the new data, so that the next time it suggests a schedule that better suits your baby's sleep patterns.

[1206] Providing psychological support

[1207] server

[1208] The server uses a generative AI model to automatically generate encouragement and advice that is sensitive to the parent's feelings. For example, the day after a night of heavy crying, the server might generate a message like, "Today was tough, but this is part of growing up. You're a great mom."

[1209] Terminal

[1210] The device will then notify the parent of this automatically generated message, allowing the parent to receive psychological support.

[1211] Individual consultation with an expert

[1212] User

[1213] Parents select the option to book a private consultation with a specialist within the app and enter the desired date and time and the details of the consultation.

[1214] Terminal

[1215] The terminal transmits the reservation information to the server.

[1216] server

[1217] The server notifies the specialist of the reservation information and obtains confirmation.

[1218] Expert

[1219] Experts will interact with parents online at designated times and provide personalized advice.

[1220] Recognizing user emotions with an emotion engine

[1221] Terminal

[1222] The text and voice data that parents enter into the app, as well as biometric information (such as heart rate and facial expressions), are sent to the emotion engine.

[1223] server

[1224] The server's emotion engine analyzes this data to determine the parent's emotional state, whether they are stressed, relieved, or experiencing a specific emotion.

[1225] Emotion-based message generation

[1226] server

[1227] Based on the analysis results of the emotion engine, the generative AI model generates a message that best suits that emotion. For example, if a parent is tired, it will generate a message such as, "Thank you for your hard work today. It's important to take a short rest."

[1228] Terminal

[1229] The generated message is sent to the device and notified to the parent, allowing the parent to receive support appropriate to the child's emotions at that time.

[1230] Specific examples

[1231] Example 1: Initial Setup and Data Entry

[1232] User: Downloads and launches the app, then enters the baby's name as "Taro," age as "6 months," and gender as "male."

[1233] Terminal: Sends the entered information to the server.

[1234] Server: Receives information, stores it in a database, and begins initial analysis.

[1235] Example 2: Schedule Generation

[1236] User: Enter sleep data (e.g., went to bed at 7pm, cried twice at night, woke up at 6am, took one hour nap at 10am and one hour nap at 2pm).

[1237] Terminal: Sends entered data to the server.

[1238] Server: Analyzes the data using a generative AI model and generates the next schedule, suggesting "go to bed at 8pm, take 1 hour and 30 minute naps at 10am and 2pm."

[1239] Example 3: Psychological support through an emotional engine

[1240] User: Texts "I'm so tired because my baby is crying at night."

[1241] Terminal: Sends the entered text data to the emotion engine on the server.

[1242] Server: The emotion engine analyzes the text and identifies that the parent is tired. The generative AI model generates a message such as, "Today was tough. It's important to take some rest."

[1243] Device: Notify parent of message.

[1244] This allows the system to not only optimize the baby's sleep schedule, but also provide support tailored to the parent's psychological state through an emotion engine, reducing stress for the parent.

[1245] The processing flow will be explained below.

[1246] Step 1:

[1247] User

[1248] Parents download the app and enter basic information about their baby (such as name, age, and gender) when they first launch it.

[1249] Step 2:

[1250] Terminal

[1251] The terminal transmits the input basic information to the server.

[1252] Step 3:

[1253] server

[1254] The server stores the received basic information about the baby in a database and prepares it for analysis.

[1255] Step 4:

[1256] User

[1257] Parents enter their child's daily sleep data (wake-up time, bedtime, nap time, frequency of nighttime crying, etc.) into the app.

[1258] Step 5:

[1259] Terminal

[1260] The device transmits the entered sleep data to the server.

[1261] Step 6:

[1262] server

[1263] The server analyzes the received sleep data and identifies the baby's sleep patterns.

[1264] Step 7:

[1265] server

[1266] Based on the analyzed data, the generative AI model generates an optimal sleep schedule based on the baby's age and developmental stage.

[1267] Step 8:

[1268] server

[1269] The generated sleep schedule is sent to the device.

[1270] Step 9:

[1271] Terminal

[1272] The device notifies the parent of the generated sleep schedule.

[1273] Step 10:

[1274] User

[1275] Parents can put their babies to sleep based on the schedule they are notified of.

[1276] Step 11:

[1277] User

[1278] Enter your actual sleep performance for that day (e.g., whether you slept as planned, how long you slept, etc.) into the app again.

[1279] Step 12:

[1280] Terminal

[1281] The terminal transmits the newly input sleep performance data to the server.

[1282] Step 13:

[1283] server

[1284] The server analyzes the new data and a generative AI model optimizes the schedule for the next day.

[1285] Step 14:

[1286] server

[1287] The optimized schedule is sent to the device again.

[1288] Step 15:

[1289] Terminal

[1290] The device will notify parents of the new schedule.

[1291] Step 16:

[1292] User

[1293] Parents input text and voice information about their daily situations and stresses into the app, and biometric information (e.g., heart rate, facial expressions, etc.) is automatically sent to the emotion engine.

[1294] Step 17:

[1295] Terminal

[1296] The device transmits the input text, voice, and biometric information to the server.

[1297] Step 18:

[1298] server

[1299] The server uses an emotion engine to analyze the parent's emotional state from the received data, determining whether the parent is stressed or relieved, for example.

[1300] Step 19:

[1301] server

[1302] Based on the results of the emotion engine, the generative AI model generates a message that best matches the parent's emotions. For example, if the parent is tired, it generates a message such as, "Thank you for your hard work today. It's important to take a short rest."

[1303] Step 20:

[1304] server

[1305] Send the generated message to the terminal.

[1306] Step 21:

[1307] Terminal

[1308] The device notifies the parent of the message, who then views the message.

[1309] Step 22:

[1310] User

[1311] Parents can schedule a private consultation with a specialist using the options within the app, inputting the desired date and time and the content of the consultation.

[1312] Step 23:

[1313] Terminal

[1314] The terminal transmits the reservation information to the server.

[1315] Step 24:

[1316] server

[1317] The server notifies the specialist of the reservation information and obtains confirmation.

[1318] Step 25:

[1319] Expert

[1320] Experts will interact with parents online at designated times and provide personalized advice.

[1321] Step 26:

[1322] User

[1323] Parents can consult with an expert through the app at a designated time and receive necessary advice.

[1324] This means that AI Nentore not only manages babies' sleep, but also provides psychological support to parents, making it a comprehensive sleep support system.

[1325] Example 2

[1326] 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."

[1327] In today's world, it is extremely difficult for parents to properly manage their baby's sleep and maintain an optimal sleep schedule. New parents, in particular, often experience stress due to a lack of knowledge about their baby's sleep patterns, which prevents them from responding appropriately. Furthermore, parents often ignore their own emotional state, which increases parenting stress. Another problem is the lack of easy access to individual consultations with specialists.

[1328] 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.

[1329] In this invention, the server includes input means for parents to input their baby's sleep data, analysis means for receiving and analyzing the data input from the input means, and schedule generation means for generating an optimal sleep schedule for the baby based on the data analyzed by the analysis means, according to the baby's age and developmental stage. This allows parents to appropriately manage their baby's sleep status and maintain an optimal sleep schedule.

[1330] The "input means" is an interface that allows parents to input their baby's sleep data and basic information.

[1331] The "analysis means" is a system for analyzing the data received from the input means and identifying the baby's sleep patterns.

[1332] The "schedule generation means" is a system for generating an optimal sleep schedule according to the baby's age and developmental stage based on the data obtained by the analysis means.

[1333] The "notification means" is a system for notifying parents of the generated sleep schedule so that the parents can be aware of the schedule.

[1334] The "schedule adjustment tool" is a system for correcting and adjusting existing sleep schedules based on new sleep data entered by parents.

[1335] The "message generating means" is a system for providing psychological support messages to parents.

[1336] The "emotion engine means" is a system for analyzing input text, voice, and biometric information to identify the parent's emotional state.

[1337] The "emotion message generating means" is a system for generating an appropriate message based on the parent's emotional state identified by the emotion engine means.

[1338] The "consultation reservation means" is a system that allows parents to make reservations for individual consultations with specialists.

[1339] This invention is a comprehensive childcare support system that combines a system that analyzes and generates an optimal sleep schedule based on the input of a parent's baby's sleep data, with an emotion engine that recognizes the user's emotions. This system aims to not only optimize a baby's sleep environment, but also to reduce the psychological burden on parents.

[1340] Enter your baby's basic information and sleep data

[1341] User

[1342] Parents first enter their baby's basic information (name, age, gender, etc.) into the app, then enter their daily sleep data (wake-up time, bedtime, nap time, frequency of nighttime crying, etc.).

[1343] Terminal

[1344] The terminal transmits the input data to the server. For example, a device equipped with a user interface, such as a smartphone or tablet, is used.

[1345] server

[1346] The server stores the received data in a database (e.g., MySQL, PostgreSQL, etc.). The stored data undergoes initial analysis using analytical tools. For example, analytical software such as Python or R can be used.

[1347] Generation and presentation of optimal sleep schedule

[1348] server

[1349] The server uses a generative AI model (e.g., OpenAI GPT-3) based on the analyzed data to generate an optimal sleep schedule for the baby based on their age and developmental stage. This schedule includes bedtime and nap times. The generated schedule is then sent to the device.

[1350] Terminal

[1351] The device will notify parents of the generated sleep schedule via a pop-up message or alert.

[1352] Schedule adjustments

[1353] User

[1354] Parents re-enter new sleep data, including whether the sleep plan was met and the actual sleep duration.

[1355] Terminal

[1356] The terminal transmits the newly entered data to the server.

[1357] server

[1358] The server will automatically adjust the schedule based on the new data, and the next suggested schedule will be revised to something like "Go to bed at 8 PM, take 1.5 hour naps at 10 AM and 2 PM."

[1359] Providing psychological support

[1360] server

[1361] The server uses a generative AI model to automatically generate encouragement and advice that is sensitive to the parent's feelings. For example, the day after a night of heavy crying, it might generate a message like, "Today was tough, but this is part of growing up. You're a great mom."

[1362] Terminal

[1363] The device notifies the parent of this automatically generated message.

[1364] Individual consultation with an expert

[1365] User

[1366] Within the app, parents select the option to book a private consultation with a specialist and enter the desired date and time and the details of the consultation.

[1367] Terminal

[1368] The terminal transmits the reservation information to the server.

[1369] server

[1370] The server notifies the specialist of the reservation information and obtains confirmation.

[1371] Expert

[1372] Experts will interact with parents online at designated times and provide personalized advice.

[1373] Recognizing user emotions with an emotion engine

[1374] Terminal

[1375] The text, voice data, and even biometric information (e.g., heart rate, facial expressions, etc.) that parents enter into the app are sent to the emotion engine.

[1376] server

[1377] The server's emotion engine analyzes this data and identifies the parent's emotional state, for example, by analyzing emotions such as "stress" or "fatigue" from the text data.

[1378] Emotion-based message generation

[1379] server

[1380] Based on the analysis results of the emotion engine, the generative AI model generates a message appropriate to that emotion. For example, if a parent is tired, it might generate a message such as, "Thank you for your hard work today. It's important to take a short rest."

[1381] Terminal

[1382] The generated message is sent to the device and notified to the parent, allowing the parent to receive support appropriate to the child's emotions at that time.

[1383] Specific examples

[1384] Example 1: Initial Setup and Data Entry

[1385] User: Downloads and launches the app, then enters the baby's name as "Taro," its age as "6 months," and its gender as "male."

[1386] Terminal: Sends the entered information to the server.

[1387] Server: Receives the information, stores it in a database, and begins initial analysis.

[1388] Example 2: Schedule Generation

[1389] User: Enter sleep data (e.g., went to bed at 7pm, cried twice at night, woke up at 6am, took one hour nap at 10am and one hour nap at 2pm).

[1390] Terminal: Sends the entered data to the server.

[1391] Server: Analyzes the data using a generative AI model and generates the next schedule, suggesting "Go to bed at 8pm, take 1 hour and 30 minute naps at 10am and 2pm."

[1392] Example 3: Psychological support through an emotional engine

[1393] User: Texts "I'm so tired because my baby is crying at night."

[1394] Terminal: Sends the entered text data to the emotion engine on the server.

[1395] Server: The emotion engine analyzes the text and identifies that the parent is tired. The generative AI model generates a message such as, "Today was tough. It's important to take some rest."

[1396] Device: Notify parent of message.

[1397] The system will be able to optimize a baby's sleep schedule and provide support tailored to the parent's psychological state through an emotion engine.

[1398] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1399] Step 1:

[1400] User

[1401] Parents download and install the app, then launch it and enter basic information about their baby (such as name, age, and gender), and then enter their baby's daily sleep data (for example, wake-up time, bedtime, nap time, and frequency of nighttime crying).

[1402] Terminal

[1403] The device sends the basic information and sleep data of the baby entered by the parent to the server in real time.

[1404] server

[1405] The server stores the received data in a database, which can be a database management system such as MySQL or PostgreSQL, and then prepares the data for initial analysis.

[1406] Step 2:

[1407] server

[1408] The server analyzes the stored data using an analytical tool, which may be data analysis software such as Python or R. The results of the analysis identify the baby's basic sleep patterns.

[1409] Input: Parent-entered baby information and sleep data

[1410] Output: Analysis of baby's sleep patterns

[1411] Step 3:

[1412] server

[1413] Based on the analysis results, the server uses a generative AI model (e.g., OpenAI GPT-3) to generate an optimal sleep schedule based on the baby's age and developmental stage, including bedtime and nap times.

[1414] Input: Analysis of baby's sleep patterns

[1415] Output: Optimal sleep schedule

[1416] Next, this generated schedule is transmitted to the terminal.

[1417] Step 4:

[1418] Terminal

[1419] The device will notify parents of the optimal sleep schedule sent from the server via pop-up messages and alerts.

[1420] User

[1421] Parents can check the notifications and use the generated sleep schedule to put their baby to bed or adjust nap times.

[1422] Enter: your optimal sleep schedule.

[1423] Output: Parental sleep schedule enforcement

[1424] Step 5:

[1425] User

[1426] Parents then enter the new sleep data into the app again, including details about whether the child was able to sleep as planned and the actual hours of sleep.

[1427] Terminal

[1428] The device sends new sleep data to the server, also in real time.

[1429] Input: New sleep data

[1430] Output: Send new sleep data

[1431] Step 6:

[1432] server

[1433] The server reanalyzes the schedule based on the newly sent sleep data and automatically adjusts it, generating and suggesting a more optimal sleep pattern for the next time.

[1434] Input: New sleep data

[1435] Output: Corrected sleep schedule

[1436] Step 7:

[1437] server

[1438] The server uses an emotion engine to understand the parent's feelings. The parent inputs text, voice data, and biometric information (e.g., heart rate, facial expression, etc.), and based on this, the parent's emotional state is identified.

[1439] Input: text, voice data, biometric information

[1440] Output: Parent's emotional state

[1441] Step 8:

[1442] server

[1443] Based on the parent's emotional state identified by the emotion engine, the generative AI model generates an appropriate message of encouragement or advice, such as, "Today was tough. It's important to take some rest."

[1444] Input: Parent emotional state

[1445] Output: An appropriate message of encouragement or advice

[1446] Step 9:

[1447] Terminal

[1448] The device will notify the parent of the generated message via a push notification or a pop-up message.

[1449] Input: A suitable message of encouragement or advice

[1450] Output: Message notification to parent

[1451] Step 10:

[1452] User

[1453] Parents can use the in-app options to schedule a private consultation with a specialist, inputting the desired topic, date and time.

[1454] Terminal

[1455] The terminal transmits the input reservation information to the server.

[1456] Input: Reservation information (consultation details, date and time)

[1457] Output: Send reservation information

[1458] Step 11:

[1459] server

[1460] The server forwards the received reservation information to the specialist and obtains confirmation of the reservation.

[1461] Input: Reservation information

[1462] Output: Coordination and confirmation with experts

[1463] Step 12:

[1464] Expert

[1465] The expert will then speak to the parent online at a confirmed date and time to provide personalized advice.

[1466] Input: Consultation received from parent

[1467] Output: Personalized advice from an expert

[1468] Through these steps, the system optimizes the baby's sleep schedule, provides support tailored to the parent's psychological state through an emotion engine, and offers expert consultations for more specific advice.

[1469] (Application example 2)

[1470] 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."

[1471] Conventional baby sleep management systems are limited to collecting and analyzing baby sleep data, and lack elements to reduce the psychological burden on parents. Furthermore, they do not provide support that takes into account the parents' emotional and stress states, making it difficult for them to maintain their mental stability. Therefore, there is a need for a more comprehensive support system that can also respond to parents' emotional states.

[1472] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1473] In this invention, the server includes input means for a parent to input sleep data of the child, analysis means for receiving and analyzing the data input from the input means, schedule generation means for generating an optimal sleep schedule according to the child's age and developmental stage based on the data analyzed by the analysis means, notification means for notifying the parent of the sleep schedule generated by the schedule generation means, schedule adjustment means for modifying or adjusting the schedule based on the new sleep data input by the parent, message generation means for providing psychological support messages to the parent, emotion analysis means for receiving and analyzing emotional data of the parent, emotion-based message generation means for generating appropriate support messages for the parent based on the emotional data analyzed by the emotion analysis means, and consultation reservation means for individual consultation with a specialist. This enables not only the optimization of the baby's sleep schedule but also support according to the parent's psychological state.

[1474] The "input means" is an interface that allows parents to input their child's sleep data and emotional state.

[1475] The "analysis means" is a means having a function of analyzing data received from the input means.

[1476] The "schedule generating means" is a means for generating an optimal sleep schedule according to the child's age and stage of development based on the data analyzed by the analyzing means.

[1477] The "notification means" is a means for notifying parents of the generated sleep schedule.

[1478] The "schedule adjustment tool" is a tool for correcting and adjusting the schedule based on new sleep data entered by the parent.

[1479] The "message generating means" is a means for providing psychological support messages to parents.

[1480] The "emotion analysis means" is a means for receiving the parent's emotion data and analyzing the parent's emotional state.

[1481] The "emotion-based message generating means" is a means for generating an appropriate support message for the parent based on the emotion data analyzed by the emotion analyzing means.

[1482] The "consultation reservation means" is a means for making a reservation for individual consultation with a specialist.

[1483] A "generative artificial intelligence model" is a machine learning model that generates optimal schedules and messages based on input data.

[1484] The present invention provides a system that analyzes a child's sleep data entered by a parent and generates and modifies an optimal sleep schedule, as well as a system that recognizes the parent's emotions and provides support messages in response to those emotions. Specific embodiments for implementing this system are described below.

[1485] Hardware and Software

[1486] Hardware:

[1487] Smartphone: Used by parents to enter data and receive notifications from the system.

[1488] Server: The central component responsible for receiving and analyzing data, generating sleep schedules, and sentiment analysis.

[1489] software:

[1490] Python 3.x: Used to implement system-wide programs.

[1491] GUI library (Tkinter): Used to build a user interface for the parent to input data.

[1492] Machine learning libraries: Used to perform data analysis, schedule generation, and emotion recognition using generative AI models.

[1493] System configuration

[1494] 1. Input method:

[1495] Parents use their smartphones to input information such as their child's sleep time, wake-up time, nap time, frequency of night crying, and emotional state into a user interface.

[1496] 2. Analysis method:

[1497] The server analyzes the data received from the input means to identify the child's sleep patterns, using a generative AI model for highly accurate analysis.

[1498] 3. Schedule generation method:

[1499] The server generates an optimal sleep schedule based on the child's age and developmental stage using a generative AI model, and the generated schedule is sent to the smartphone.

[1500] 4. Means of notification:

[1501] The generated sleep schedule is sent to parents' smartphones, helping them put their children to bed at realistic times.

[1502] 5. Scheduling methods:

[1503] When parents enter new sleep data, the server automatically adjusts the schedule based on that data and provides the optimal schedule again.

[1504] 6. Message Generation Method:

[1505] The server uses the generative AI model to provide parents with psychological support messages, such as "Today was tough, but it's part of growing up. You're a great mom" the day after a night of heavy crying.

[1506] 7. Emotion analysis means:

[1507] The system analyzes parental input, including text, voice, and biometric information (heart rate, facial expressions, etc.) to identify the child's emotional state. Emotion analysis is also performed using a generative AI model.

[1508] 8. Emotion-based message generation method:

[1509] Based on the results of emotion analysis, a support message is generated. For example, if the system detects that a parent is "tired," it generates a message such as "Thank you for your hard work today. It's important to take a short rest."

[1510] 9. How to book a consultation:

[1511] It provides a user interface for parents to book individual consultations with specialists. The booking information is sent to the server and confirmed and approved by the specialist.

[1512] Specific examples

[1513] Example 1: Initial Setup and Data Entry

[1514] The parent downloads and launches the app, entering the child's name as "Taro," age as "6 months," and gender as "male."

[1515] The smartphone sends the entered information to the server, which stores the received information in a database and begins initial analysis.

[1516] Example 2: Schedule Generation

[1517] Parents enter sleep data (e.g., baby goes to bed at 7pm, cries twice at night, wakes up at 6am, takes one-hour naps at 10am and 2pm).

[1518] The smartphone sends the input data to the server, which then analyzes it using a generative AI model to generate the next schedule.

[1519] The generated schedule suggests "go to bed at 8pm, take 1 hour and 30 minute naps at 10am and 2pm."

[1520] Example 3: Psychological support through an emotional engine

[1521] A parent texts, "I'm so tired because my baby is crying at night."

[1522] The smartphone sends the entered text data to the server's emotion engine, which analyzes the text and determines that the parent is tired.

[1523] The generative AI model generates messages such as, "Today was tough. It's important to take some rest."

[1524] A message is sent to the smartphone, and parents can receive psychological support.

[1525] Example prompt sentence:

[1526] Please enter your baby's basic information. Name: "Taro", Age: "6 months", Gender: Do not enter

[1527] Next, enter your baby's sleep data: Wake-up time: "06:00", Bedtime: "20:00", Nap time: "2 times, 1 hour each", Night crying: "2 times"

[1528] Enter your emotion. Emotion: "I'm tired."

[1529] In this manner, the present invention can optimize the baby's sleep schedule as well as provide support according to the parent's emotional state, thereby comprehensively supporting the sleep environment for both parent and baby.

[1530] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1531] Step 1:

[1532] Parents enter basic information about their children.

[1533] How it works: The user (parent) uses the smartphone's user interface to enter basic information about their child, such as their name, age, and gender.

[1534] Input: Name, age, gender

[1535] Output: Basic information data

[1536] Data processing: The basic information entered is sent from the smartphone to the server.

[1537] Step 2:

[1538] An initial analysis is performed based on basic information.

[1539] Operation: The server stores the received basic information in a database and begins initial analysis. Based on the analysis results, it prepares for initial configuration.

[1540] Input: Basic information data

[1541] Output: Analysis result data

[1542] Data calculation: Analyze basic information and generate basic analysis results according to the child's age.

[1543] Step 3:

[1544] Parents enter their child's sleep data.

[1545] Operation: The user (parent) uses the smartphone's user interface to input their child's sleep data (e.g., wake-up time, bedtime, nap time, frequency of night crying, etc.).

[1546] Input: Sleep data (wake-up time, bedtime, nap time, frequency of night crying)

[1547] Output: Sleep data

[1548] Data processing: The entered sleep data is sent from the smartphone to the server.

[1549] Step 4:

[1550] Analyzes sleep data and generates an optimal sleep schedule.

[1551] How it works: The server analyzes the input sleep data using a generative AI model and generates an optimal sleep schedule based on the child's age and developmental stage.

[1552] Input: Sleep data

[1553] Output: Optimal sleep schedule

[1554] Data Computing: Generative AI models are used to analyze data and generate schedules.

[1555] Step 5:

[1556] The generated sleep schedule is notified to the parent.

[1557] How it works: The server notifies the smartphone of the generated optimal sleep schedule, and the user (parent) receives the notification.

[1558] Enter: optimal sleep schedule

[1559] Output: Notification message

[1560] Data processing: The generated schedule is processed into a notification message and sent to the smartphone.

[1561] Step 6:

[1562] Parents enter new sleep data and reschedule.

[1563] How it works: The user (parent) re-enters sleep data, and the server automatically readjusts the schedule based on that data.

[1564] Input: New sleep data

[1565] Output: A recalibrated optimal sleep schedule

[1566] Data calculations: Recalculate the schedule based on new data using generative AI models.

[1567] Step 7:

[1568] Parental emotional data is input and the emotional state is analyzed.

[1569] Operation: The user (parent) inputs emotional data (text, voice, biometric information, etc.) using the smartphone's user interface. The server analyzes the emotional data using emotion analysis means and identifies the parent's emotional state.

[1570] Input: Emotion data

[1571] Output: Emotion analysis results

[1572] Data processing: The emotional data is analyzed using emotion analysis means to identify the emotional state of the parents.

[1573] Step 8:

[1574] A support message based on the results of emotion analysis is generated and notified to the parent.

[1575] How it works: Based on the results of emotion analysis, the server uses a generative AI model to generate an appropriate support message for the parent. The generated message is then sent to the smartphone.

[1576] Input: Sentiment analysis results

[1577] Output: Support message

[1578] Data calculation: Based on the results of sentiment analysis, a generative AI model generates support messages.

[1579] Step 9:

[1580] Book a private consultation with an expert.

[1581] Operation: The user (parent) makes an appointment with a specialist using the user interface on their smartphone. The appointment information is sent to the server and notified to the specialist.

[1582] Input: Reservation information (desired date and time, consultation details, etc.)

[1583] Output: Reservation confirmation message

[1584] Data processing: The reservation information is sent to the server and notified to the specialist.

[1585] 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.

[1586] 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.

[1587] 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.

[1588] [Third embodiment]

[1589] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1590] 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.

[1591] 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).

[1592] 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.

[1593] 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.

[1594] 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).

[1595] 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.

[1596] 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.

[1597] 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.

[1598] 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.

[1599] 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.

[1600] 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."

[1601] This invention is a system that automatically generates and modifies an optimal sleep schedule based on the analysis of sleep data entered by parents. The purpose of this system is to provide comprehensive support for the sleep environment of parents and babies.

[1602] Program processing overview

[1603] Enter your baby's basic information and sleep data

[1604] User

[1605] Parents first enter their baby's basic information (name, age, gender, etc.) into the app, then enter their daily sleep data (wake-up time, bedtime, nap time, frequency of nighttime crying, etc.).

[1606] Terminal

[1607] The terminal transmits the input data to the server.

[1608] server

[1609] The server stores the received data in a database and analyzes it to identify the baby's sleep patterns.

[1610] Generation and presentation of optimal sleep schedule

[1611] server

[1612] The server then generates an optimal sleep schedule for the baby based on the baby's sleep patterns, including bedtime and daytime naps, and sends the schedule to the device.

[1613] Terminal

[1614] The device will then notify the parents of the generated sleep schedule, allowing them to get their baby to sleep based on this schedule.

[1615] Schedule adjustments

[1616] User

[1617] Parents will then re-enter any new sleep data their baby actually had, including whether they slept as planned and the actual hours of sleep.

[1618] Terminal

[1619] The terminal transmits the newly entered data to the server.

[1620] server

[1621] The server automatically adjusts the schedule based on the new data it receives, so that the next time it suggests a schedule that better suits your baby's sleep patterns.

[1622] Providing psychological support

[1623] server

[1624] To ease the psychological burden on parents, the server uses a generative AI model to automatically generate encouraging messages and advice. For example, the server might generate a message the day after a night of heavy crying, such as, "Today was tough, but it's part of growing up. You're a great mom."

[1625] Terminal

[1626] The device will then notify the parent of this automatically generated message, allowing the parent to receive psychological support.

[1627] Individual consultation with an expert

[1628] User

[1629] Parents can schedule a private consultation with a specialist within the app. For example, they can press the "Book a consultation" button and enter the desired date and time and the content of the consultation.

[1630] Terminal

[1631] The terminal transmits the reservation information to the server.

[1632] server

[1633] The server notifies the specialist of the reservation information and obtains confirmation.

[1634] Expert

[1635] Experts will interact with parents online at designated times and provide personalized advice.

[1636] Specific examples

[1637] Example 1: Initial Setup and Data Entry

[1638] User: Downloads and launches the app, then enters the baby's name as "Taro," age as "6 months," and gender as "male."

[1639] Terminal: Sends the entered information to the server.

[1640] Server: Receives information, stores it in a database, and begins initial analysis.

[1641] Example 2: Schedule Generation

[1642] User: Enter sleep data (e.g., went to bed at 7pm, cried twice at night, woke up at 6am, took one hour nap at 10am and one hour nap at 2pm).

[1643] Terminal: Sends entered data to the server.

[1644] Server: Analyzes the data using a generative AI model and generates the next schedule, suggesting "go to bed at 8pm, take 1 hour and 30 minute naps at 10am and 2pm."

[1645] Example 3: Providing psychological support messages

[1646] Server: After a series of nights of constant crying, the server automatically generates a message like, "Today was tough, but don't worry, it's part of growing up."

[1647] Device: Notifies parents of messages, giving them peace of mind.

[1648] This system allows parents to properly manage their baby's sleep and create an optimal sleeping environment with the help of expert advice. It also contributes to reducing stress for parents through psychological support. In this way, the present invention can improve the quality of sleep for both parents and babies.

[1649] The processing flow will be explained below.

[1650] Step 1:

[1651] User

[1652] Parents download the app and enter basic information about their baby (such as name, age, and gender) when they first launch it.

[1653] Step 2:

[1654] Terminal

[1655] The terminal transmits the input basic information to the server.

[1656] Step 3:

[1657] server

[1658] The server stores the received basic information about the baby in a database and prepares it for analysis.

[1659] Step 4:

[1660] User

[1661] Parents enter sleep data from the past 24 hours (wake-up time, bedtime, nap time, frequency of nighttime crying, etc.) into the app.

[1662] Step 5:

[1663] Terminal

[1664] The terminal transmits the input sleep data to the server.

[1665] Step 6:

[1666] server

[1667] The server analyzes the received sleep data to identify the baby's sleep patterns, which are then used to further analyze the data using a generative AI model.

[1668] Step 7:

[1669] server

[1670] The server uses a generative AI model to generate an optimal sleep schedule for the baby based on their age and developmental stage, including nighttime bedtime and daytime nap times.

[1671] Step 8:

[1672] server

[1673] The generated sleep schedule is sent to the device.

[1674] Step 9:

[1675] Terminal

[1676] The device will then notify the parent of the received sleep schedule, which the parent can then view on the app.

[1677] Step 10:

[1678] User

[1679] Parents can put their babies to sleep based on the schedule they are notified of.

[1680] Step 11:

[1681] User

[1682] Parents will then again enter the actual sleep performance for that day (e.g., whether they went to bed as planned, how long they slept, etc.) into the app.

[1683] Step 12:

[1684] Terminal

[1685] The terminal transmits the newly input sleep performance data to the server.

[1686] Step 13:

[1687] server

[1688] The server analyzes the new data and uses a generative AI model to optimize the schedule for the next day.

[1689] Step 14:

[1690] server

[1691] The new optimized schedule is sent to the device.

[1692] Step 15:

[1693] Terminal

[1694] The device will notify the parent of the new schedule and allow them to run it again.

[1695] Step 16:

[1696] server

[1697] The server uses a generative AI model to automatically generate messages aimed at providing psychological support to parents, including encouragement and advice.

[1698] Step 17:

[1699] server

[1700] Send the generated message to the terminal.

[1701] Step 18:

[1702] Terminal

[1703] The device will notify the parent of the message, who can then view it.

[1704] Step 19:

[1705] User

[1706] Parents select the option within the app to schedule a private consultation with a specialist, inputting the desired date and time and the details of the consultation.

[1707] Step 20:

[1708] Terminal

[1709] The terminal transmits the reservation information to the server.

[1710] Step 21:

[1711] server

[1712] The server notifies the specialist of the reservation information and obtains confirmation.

[1713] Step 22:

[1714] Expert

[1715] Experts will interact with parents online at designated times and provide personalized advice.

[1716] Step 23:

[1717] User

[1718] Parents can consult with an expert through the app at a designated time and receive necessary advice.

[1719] These steps guide the system through a series of processes to improve the baby's sleep quality and reduce stress for parents.

[1720] Example 1

[1721] 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."

[1722] Babies' sleep patterns vary greatly from baby to baby, making it extremely difficult for parents to establish an appropriate sleep schedule. As a result, parents often spend a lot of time and effort managing their baby's sleep, and become stressed. Furthermore, to receive specialized advice tailored to the baby's developmental stage, individual consultations with specialists are required, which is also time-consuming. Traditional methods make it difficult to comprehensively resolve these issues.

[1723] 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.

[1724] In this invention, the server includes an input means for a parent to input their baby's sleep data, an analysis means for receiving and analyzing the data input from the input means, a schedule generation means for generating an optimal sleep schedule based on the baby's age and developmental stage based on the data analyzed by the analysis means, a notification means for notifying the parent of the sleep schedule generated by the schedule generation means, a schedule adjustment means for modifying or adjusting the schedule based on the new sleep data input by the parent, a message generation means for providing psychological support messages to the parent, a consultation reservation means for individual consultations with a specialist, a transmission means for transmitting the data input from the input means to the server, a storage means for the server to store the baby's sleep data in a database, and a means for the analysis means to analyze the sleep patterns using a generative artificial intelligence model. This allows parents to automatically generate or modify an optimal sleep schedule based on their baby's individual sleep patterns and support their baby's development through psychological support messages and individual consultations with a specialist.

[1725] 1. "Input means" refers to a device or interface that allows parents to input their baby's sleep data.

[1726] 2. "Analysis means" refers to the device or algorithm used to analyze the input data and identify the baby's sleep patterns.

[1727] 3. "Schedule generation means" refers to a device or algorithm that creates an optimal sleep schedule based on the baby's age and developmental stage based on analyzed data.

[1728] 4. "Notification means" refers to a device or system that notifies parents of the generated sleep schedule.

[1729] 5. "Schedule Adjustment Tool" means a device or algorithm that modifies or adjusts a sleep schedule based on new sleep data entered by a parent.

[1730] 6. "Message generation means" refers to a device or system for generating and providing psychological support messages to parents.

[1731] 7. "Consultation booking means" refers to a device or system for booking an individual consultation with a specialist.

[1732] 8. "Transmission means" refers to a device or system for transmitting data entered through the input means to the server.

[1733] 9. "Storage means" refers to the device or system that allows the server to store the baby's sleep data in a database.

[1734] 10. "Generative AI model" refers to a machine learning algorithm that analyzes input data to understand and predict a baby's sleep patterns.

[1735] The present invention is a system that allows parents to input their baby's sleep data, analyzes the data, and automatically generates and modifies an optimal sleep schedule. The purpose of this system is to provide comprehensive support for the sleep environment of parents and babies. The following describes an embodiment of this system.

[1736] Enter your baby's basic information and sleep data

[1737] User

[1738] Parents use a smartphone app to enter basic information about their baby (such as name, age in months, and gender). The user then uses the app's input form to enter data, providing information such as the baby's name as "Taro," its age as "6 months," and its gender as "male." The parent then enters daily sleep data (such as wake-up time, bedtime, nap time, and frequency of nighttime crying) in the same way.

[1739] Sending input data

[1740] Terminal

[1741] The terminal organizes the data entered by the user and sends it to the server using a secure communication protocol (e.g. HTTPS). All entered data is encrypted and securely transferred to the server.

[1742] Data storage and analysis

[1743] server

[1744] The server stores the received user data in a database (e.g., MySQL). The stored data is indexed and organized for efficient search and analysis. The server then uses data analysis software, such as Python scripts, to analyze the sleep data and identify the baby's sleep patterns. Generative artificial intelligence models (generative AI models) are used in the analysis to improve the accuracy of data processing.

[1745] Generating an optimal sleep schedule

[1746] server

[1747] The server generates an optimal sleep schedule based on the identified baby's sleep patterns and developmental stage. A generative AI model (e.g., a model using TensorFlow) is used for generation. The model receives a prompt: "Please suggest a new sleep schedule based on the current sleep patterns of a 6-month-old baby." The server generates a new schedule as a prediction.

[1748] Schedule Notifications

[1749] Terminal

[1750] The device then notifies the parent of the optimal sleep schedule received from the server. The schedule is displayed on the parent's smartphone using the push notification function. For example, a specific schedule such as "Go to bed at 8 p.m., take 1.5 hour naps at 10 a.m. and 2 p.m." may be displayed.

[1751] Entering new sleep data

[1752] User

[1753] Parents then enter their baby's new sleep data into the app again, using a dedicated form in the app to record the actual number of hours of sleep, the number of nighttime crying episodes, and the length of naps in detail.

[1754] Rescheduling

[1755] Terminal

[1756] The device then sends the newly entered sleep data to the server, again via a secure communications protocol.

[1757] server

[1758] The server re-analyzes the current sleep schedule based on the new data received and automatically adjusts the schedule as needed, using machine learning algorithms to update the schedule based on the baby's latest sleep patterns.

[1759] Generating psychological support messages

[1760] server

[1761] The server automatically generates an encouraging message using a generative AI model (e.g., GPT-3) to provide psychological support to parents. An example of a prompt is "Please create an encouraging message for a parent whose child is crying a lot at night.", and generates an encouraging message for the parent.

[1762] Message notifications

[1763] Terminal

[1764] The device will then notify the parent of the generated encouraging message via an in-app message box or push notification, so the parent can see it immediately.

[1765] Book a private consultation with an expert

[1766] User

[1767] Parents press the "Book a consultation" button in the app and enter the desired date and time and the content of the consultation.

[1768] Terminal

[1769] The terminal transmits the reservation information input by the user to the server.

[1770] server

[1771] The server notifies the relevant specialist of the received reservation information, and the specialist prepares to interact with the parent online at the specified time and provide individual advice.

[1772] In this way, the present invention can provide a concrete means for improving the quality of sleep for parents and their babies, allowing parents to effectively manage their babies' sleep and reduce stress.

[1773] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1774] Step 1:

[1775] User

[1776] Parents launch the smartphone app and enter basic information about their baby (such as name, age in months, and gender). The data is entered in the format of "baby's name," "age in months," and "gender." Based on this, the app stores the information entered in the fields in an internal data structure.

[1777] Input: Baby's basic information (e.g. name, age, sex)

[1778] Output: Basic information stored in the app's internal data structures

[1779] Step 2:

[1780] Terminal

[1781] The terminal organizes the data entered by the user and sends it to the server using a secure communication protocol (e.g., HTTPS). The data for each field is serialized in JSON format or similar and sent to the server in encrypted form.

[1782] Input: Basic baby information

[1783] Output: Basic information sent to the server

[1784] Step 3:

[1785] server

[1786] The server stores the received user data in a database (e.g., MySQL), which is then indexed using a database management system and prepared for efficient later searching and analysis.

[1787] Input: Baby data sent from the device

[1788] Output: Baby data stored in a database

[1789] Step 4:

[1790] User

[1791] Parents enter daily sleep data (wake-up time, bedtime, nap time, nighttime crying frequency, etc.) into the app. As data is entered into input fields, the app stores it in an internal data structure.

[1792] Input: Sleep data (e.g., wake-up time, bedtime, nap time, frequency of night crying)

[1793] Output: Sleep data stored in the app's internal data structure

[1794] Step 5:

[1795] Terminal

[1796] The device organizes the sleep data entered by the user and sends it to the server using a secure communication protocol (e.g., HTTPS). The data is serialized in JSON format, encrypted, and sent to the server.

[1797] Input: Sleep data

[1798] Output: Sleep data sent to the server

[1799] Step 6:

[1800] server

[1801] The server stores the received sleep data in a database. It also analyzes the sleep data using analysis software such as Python scripts. A generative AI model is used for the analysis to identify the baby's sleep patterns. For example, the prompt sentence is "Based on the baby's sleep data, please identify the sleep patterns."

[1802] Input: Sleep data

[1803] Data processing / calculation: Analysis using generative AI models

[1804] Output: Identified sleep patterns

[1805] Step 7:

[1806] server

[1807] The server uses a generative AI model to generate an optimal sleep schedule based on the identified sleep patterns and age. The server generates a new schedule using the prompt, "Please suggest a new sleep schedule based on the current sleep patterns of a 6-month-old baby."

[1808] Input: Identified sleep pattern, age in months

[1809] Data processing / calculation: Schedule generation using generative AI models

[1810] Output: Optimal sleep schedule

[1811] Step 8:

[1812] Terminal

[1813] The device notifies the user of the optimal sleep schedule received from the server, and the schedule is displayed on the parent's smartphone using the push notification function.

[1814] Enter: your optimal sleep schedule.

[1815] Output: Sleep schedule notified to parent

[1816] Step 9:

[1817] User

[1818] The parent re-enters the new sleep data into the app, which updates the app's internal data structures.

[1819] Input: New sleep data

[1820] Output: New sleep data stored in the app's internal data structure.

[1821] Step 10:

[1822] Terminal

[1823] The device then sends the newly entered data to the server, again via a secure communications protocol.

[1824] Input: New sleep data

[1825] Output: New sleep data sent to the server.

[1826] Step 11:

[1827] server

[1828] The server reanalyzes the current schedule based on the new data received and automatically adjusts the schedule. Machine learning algorithms are used to update the optimal schedule based on the new data.

[1829] Input: New sleep data

[1830] Data processing / calculation: Reanalysis using machine learning algorithms

[1831] Output: Adjusted schedule

[1832] Step 12:

[1833] server

[1834] The server automatically generates encouraging messages using a generative AI model to provide psychological support to parents. The message is generated based on the prompt, "Please create an encouraging message for parents whose child has been crying a lot at night."

[1835] Input: Sleep data, generative AI model

[1836] Data processing / calculation: Message generation using generative AI models

[1837] Output: An encouraging message

[1838] Step 13:

[1839] Terminal

[1840] The device will then notify the parent of the generated encouraging message via a message box within the app or a push notification.

[1841] Input: An encouraging message

[1842] Output: Message sent to parent

[1843] Step 14:

[1844] User

[1845] Parents press the "Book a consultation" button in the app and enter the desired date and time and the content of the consultation.

[1846] Input: Reservation information (desired date and time, consultation details)

[1847] Output: Reservation information stored in the app's internal data structure

[1848] Step 15:

[1849] Terminal

[1850] The terminal transmits the reservation information input by the user to the server.

[1851] Input: Reservation information

[1852] Output: Reservation information sent to the server

[1853] Step 16:

[1854] server

[1855] The server notifies the relevant specialist of the received reservation information and prepares the specialist to interact with the parent online at the specified time.

[1856] Input: Reservation information

[1857] Output: Booking information notified to the expert

[1858] In this way, all the steps work together to form a system that provides a holistic supportive sleep environment for parents and babies.

[1859] (Application example 1)

[1860] 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."

[1861] As autonomous vehicle technology evolves, driver health and sleep management are becoming important issues for accident prevention and safe driving. Drivers driving long distances in particular need to be able to take appropriate breaks and receive immediate warnings when they feel drowsy. However, conventional systems often cannot meet these needs, so there is a need for technology that can accurately grasp the driver's health and psychological burden, and generate and notify optimal break schedules based on that information.

[1862] 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.

[1863] In this invention, the server includes input means for the driver to input sleep data, analysis means for receiving and analyzing the data input from the input means, schedule generation means for generating an optimal rest schedule according to the driver's health state based on the data analyzed by the analysis means, notification means for notifying the driver of the rest schedule generated by the schedule generation means, schedule adjustment means for correcting and adjusting the schedule based on the new sleep data input by the driver, message generation means for providing the driver with a psychological support message, and consultation reservation means for individual consultation with a specialist. This makes it possible to accurately grasp the driver's health state and psychological burden, and to generate and notify the optimal rest schedule and issue immediate warnings based on that information.

[1864] "Driver" means a person who uses or controls an automated vehicle.

[1865] "Sleep data" refers to information entered by the driver, such as the amount of sleep, wake-up time, rest time, and frequency of drowsiness.

[1866] "Input means" means a device or interface through which a driver inputs sleep data.

[1867] The "analysis means" refers to software or hardware for analyzing the sleep data received from the input means.

[1868] The "schedule generation means" is a system that creates an optimal rest schedule according to the driver's health condition based on the data analyzed by the analysis means.

[1869] The "notification means" refers to a device or interface for notifying the driver of the generated rest schedule.

[1870] The "schedule adjustment tool" refers to a system that modifies and adjusts existing schedules based on newly entered sleep data by drivers.

[1871] The "message generating means" refers to a system that generates psychological support messages for the driver.

[1872] A "consultation reservation means" is a device or interface that accepts reservations for individual consultations with experts.

[1873] A "generative AI model" is an artificial intelligence algorithm or system for analyzing data and generating messages.

[1874] This invention is a system for supporting the health and sleep management of drivers of self-driving vehicles, and is realized by the following steps.

[1875] System Overview

[1876] 1. Enter your sleep data

[1877] User: First, the driver installs the app and enters basic information (name, age, gender, etc.), then enters daily sleep data (wake-up time, bedtime, rest time, frequency of drowsiness, etc.).

[1878] Device: Use a device such as a smartphone or head-mounted display to send the input data to the server.

[1879] Server: The server stores the received data in a database (e.g., MySQL).

[1880] 2. Data analysis and schedule generation

[1881] Server: The server uses a generative AI model (such as TensorFlow) to analyze the stored data. The analytical model identifies the driver's health and sleep patterns.

[1882] Server: Based on the analysis results, the schedule generation means generates an optimal break schedule, which includes break timing and recommended break duration.

[1883] 3. Schedule notification and adjustment

[1884] Terminal: The generated rest schedule is communicated to the driver via smart glasses or a head-mounted display.

[1885] User: The driver re-enters new sleep data (e.g., unplanned nap, actual rest time, etc.).

[1886] Terminal: New data entered is sent to the server.

[1887] Server: Based on the new data, the schedule generator automatically adjusts the schedule and applies it next time, providing a more accurate break schedule.

[1888] 4. Real-time warning system

[1889] Server: The analysis means determines the driver's drowsiness in real time.

[1890] Device: When the driver feels drowsy, a warning message is displayed on smart glasses or a head-mounted display.

[1891] 5. Providing psychological support messages

[1892] Server: The server uses a generative AI model to automatically generate encouraging and advice messages, such as "You had a hard time today, but this is part of your growth. You're a great driver."

[1893] Device: This message is sent to the driver via smart glasses or a head-mounted display, allowing the driver to receive psychological support.

[1894] 6. Individual consultation with an expert

[1895] User: Drivers can schedule a private consultation with a sleep specialist within the app by pressing the "Book a Consultation" button and entering the desired date and time and the details of the consultation.

[1896] Terminal: The reservation information is sent to the server.

[1897] Server: The server notifies the expert of the reservation information and gets confirmation.

[1898] Experts: Experts will interact with drivers online at designated times and provide personalized advice.

[1899] Specific examples

[1900] Example prompt sentence:

[1901] User: Enter the driver's name, age, gender, and daily sleep data.

[1902] System: The proposed break time is 14:00. Please take a one-hour break now.

[1903] System: You are feeling drowsy. We recommend you take a break or seek professional advice.

[1904] System: You've had a tough day, but good luck. You're a great driver.

[1905] This system allows drivers to properly manage their health and receive expert advice to create an optimal rest environment. It also helps reduce driver stress through psychological support. This will improve the safety of autonomous vehicles and reduce the risk of accidents.

[1906] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1907] Step 1:

[1908] User: The driver installs the app and enters basic information (name, age, gender, etc.) Once this basic information is entered, the device sends it to the server.

[1909] Input: Driver's name, age, gender

[1910] Output: Send basic information to the server

[1911] Step 2:

[1912] Device: The driver enters their daily sleep data (wake-up time, bedtime, rest time, frequency of drowsiness, etc.) into the app. The device then sends this data to the server.

[1913] Input: Driver sleep duration, wake-up time, rest time, frequency of drowsiness

[1914] Output: Send sleep data to the server

[1915] Step 3:

[1916] Server: The server stores the received basic information and daily sleep data in a database (e.g., MySQL). The stored data is analyzed using a generative AI model (e.g., TensorFlow).

[1917] Input: Basic information and sleep data to the server

[1918] Output: Data storage in database, data analysis using analytical model

[1919] Step 4:

[1920] Server: Based on the data analyzed using the generative AI model, the driver's health condition and sleep patterns are identified. Based on the analysis results, the server generates an optimal rest schedule using a schedule generation tool.

[1921] Input: Analyzed sleep data

[1922] Output: Generate an optimal break schedule

[1923] Step 5:

[1924] Terminal: The generated rest schedule is notified to the driver via smart glasses or a head-mounted display. The schedule information is displayed in real time using the notification method.

[1925] Input: Break schedule from schedule generator

[1926] Output: Notify driver of break schedule

[1927] Step 6:

[1928] User: The driver enters new sleep data (e.g., unplanned naps, actual rest times, etc.) into the device. The device sends the new data to the server.

[1929] Input: New sleep data

[1930] Output: Send new data to the server

[1931] Step 7:

[1932] Server: Based on the new sleep data, the server recalculates and adjusts the existing rest schedule using the schedule adjustment method.

[1933] Input: New sleep data

[1934] Output: Generate an adjusted break schedule

[1935] Step 8:

[1936] Device: The adjusted break schedule is notified to the driver, and the device displays the adjusted schedule in real time.

[1937] Input: Adjusted break schedule

[1938] Output: Notification of adjusted schedule to driver

[1939] Step 9:

[1940] Server: The analysis means determines the driver's drowsiness in real time. If drowsiness is detected, the server immediately generates a warning message.

[1941] Input: Real-time driver status data

[1942] Output: Generate a warning message

[1943] Step 10:

[1944] Device: When a driver feels drowsy, a warning message will appear on the smart glasses or head-mounted display, prompting them to take an immediate break.

[1945] Input: warning message

[1946] Output: Notify driver of warning message

[1947] Step 11:

[1948] Server: The server uses a generative AI model to automatically generate encouraging and advice messages, such as "You had a hard time today, but this is part of your growth. You're a great driver."

[1949] Input: Driver sleep and health data

[1950] Output: Generates encouraging and advice messages

[1951] Step 12:

[1952] Device: The generated psychological support message is sent to the driver via smart glasses or a head-mounted display.

[1953] Input: Support message

[1954] Output: Notify driver of support message

[1955] Step 13:

[1956] Users: Drivers can book a private consultation with a sleep specialist within the app by entering the desired date and time and the details of the consultation.

[1957] Input: Consultation reservation information

[1958] Output: Send reservation information to the server

[1959] Step 14:

[1960] Server: The reservation information is stored on the server and notified to the expert. An online dialogue with the expert is prepared.

[1961] Input: Consultation reservation data

[1962] Output: Expert notification and confirmation

[1963] Step 15:

[1964] Experts: Experts will interact with drivers online at designated times and provide personalized advice.

[1965] Input: Consultation details from the driver, reservation information

[1966] Output: Expert advice

[1967] 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.

[1968] This system combines a system that allows parents to input their baby's sleep data, analyzes it, and generates and modifies an optimal sleep schedule, with an emotion engine that recognizes the user's emotions. The system aims to provide comprehensive support for the sleep environment of parents and babies, and reduce the psychological burden on parents.

[1969] Program processing overview

[1970] Enter your baby's basic information and sleep data

[1971] User

[1972] Parents first enter their baby's basic information (name, age, gender, etc.) into the app, then enter their daily sleep data (wake-up time, bedtime, nap time, frequency of nighttime crying, etc.).

[1973] Terminal

[1974] The terminal transmits the input data to the server.

[1975] server

[1976] The server stores the received data in a database and analyzes the information, which can then be used to identify the baby's sleep patterns.

[1977] Generation and presentation of optimal sleep schedule

[1978] server

[1979] The server uses the generative AI model to generate an optimal sleep schedule for the baby based on their age and developmental stage, including bedtime and daytime naps, and then sends the schedule to the device.

[1980] Terminal

[1981] The device will then notify the parents of the generated sleep schedule, allowing them to get their baby to sleep based on this schedule.

[1982] Schedule adjustments

[1983] User

[1984] Parents will then re-enter any new sleep data their baby actually had, including whether they slept as planned and the actual hours of sleep.

[1985] Terminal

[1986] The terminal transmits the newly entered data to the server.

[1987] server

[1988] The server automatically adjusts the schedule based on the new data, so that the next time it suggests a schedule that better suits your baby's sleep patterns.

[1989] Providing psychological support

[1990] server

[1991] The server uses a generative AI model to automatically generate encouragement and advice that is sensitive to the parent's feelings. For example, the day after a night of heavy crying, the server might generate a message like, "Today was tough, but this is part of growing up. You're a great mom."

[1992] Terminal

[1993] The device will then notify the parent of this automatically generated message, allowing the parent to receive psychological support.

[1994] Individual consultation with an expert

[1995] User

[1996] Parents select the option to book a private consultation with a specialist within the app and enter the desired date and time and the details of the consultation.

[1997] Terminal

[1998] The terminal transmits the reservation information to the server.

[1999] server

[2000] The server notifies the specialist of the reservation information and obtains confirmation.

[2001] Expert

[2002] Experts will interact with parents online at designated times and provide personalized advice.

[2003] Recognizing user emotions with an emotion engine

[2004] Terminal

[2005] The text and voice data that parents enter into the app, as well as biometric information (such as heart rate and facial expressions), are sent to the emotion engine.

[2006] server

[2007] The server's emotion engine analyzes this data to determine the parent's emotional state, whether they are stressed, relieved, or experiencing a specific emotion.

[2008] Emotion-based message generation

[2009] server

[2010] Based on the analysis results of the emotion engine, the generative AI model generates a message that best suits that emotion. For example, if a parent is tired, it will generate a message such as, "Thank you for your hard work today. It's important to take a short rest."

[2011] Terminal

[2012] The generated message is sent to the device and notified to the parent, allowing the parent to receive support appropriate to the child's emotions at that time.

[2013] Specific examples

[2014] Example 1: Initial Setup and Data Entry

[2015] User: Downloads and launches the app, then enters the baby's name as "Taro," age as "6 months," and gender as "male."

[2016] Terminal: Sends the entered information to the server.

[2017] Server: Receives information, stores it in a database, and begins initial analysis.

[2018] Example 2: Schedule Generation

[2019] User: Enter sleep data (e.g., went to bed at 7pm, cried twice at night, woke up at 6am, took one hour nap at 10am and one hour nap at 2pm).

[2020] Terminal: Sends entered data to the server.

[2021] Server: Analyzes the data using a generative AI model and generates the next schedule, suggesting "go to bed at 8pm, take 1 hour and 30 minute naps at 10am and 2pm."

[2022] Example 3: Psychological support through an emotional engine

[2023] User: Texts "I'm so tired because my baby is crying at night."

[2024] Terminal: Sends the entered text data to the emotion engine on the server.

[2025] Server: The emotion engine analyzes the text and identifies that the parent is tired. The generative AI model generates a message such as, "Today was tough. It's important to take some rest."

[2026] Device: Notify parent of message.

[2027] This allows the system to not only optimize the baby's sleep schedule, but also provide support tailored to the parent's psychological state through an emotion engine, reducing stress for the parent.

[2028] The processing flow will be explained below.

[2029] Step 1:

[2030] User

[2031] Parents download the app and enter basic information about their baby (such as name, age, and gender) when they first launch it.

[2032] Step 2:

[2033] Terminal

[2034] The terminal transmits the input basic information to the server.

[2035] Step 3:

[2036] server

[2037] The server stores the received basic information about the baby in a database and prepares it for analysis.

[2038] Step 4:

[2039] User

[2040] Parents enter their child's daily sleep data (wake-up time, bedtime, nap time, frequency of nighttime crying, etc.) into the app.

[2041] Step 5:

[2042] Terminal

[2043] The device transmits the entered sleep data to the server.

[2044] Step 6:

[2045] server

[2046] The server analyzes the received sleep data and identifies the baby's sleep patterns.

[2047] Step 7:

[2048] server

[2049] Based on the analyzed data, the generative AI model generates an optimal sleep schedule based on the baby's age and developmental stage.

[2050] Step 8:

[2051] server

[2052] The generated sleep schedule is sent to the device.

[2053] Step 9:

[2054] Terminal

[2055] The device notifies the parent of the generated sleep schedule.

[2056] Step 10:

[2057] User

[2058] Parents can put their babies to sleep based on the schedule they are notified of.

[2059] Step 11:

[2060] User

[2061] Enter your actual sleep performance for that day (e.g., whether you slept as planned, how long you slept, etc.) into the app again.

[2062] Step 12:

[2063] Terminal

[2064] The terminal transmits the newly input sleep performance data to the server.

[2065] Step 13:

[2066] server

[2067] The server analyzes the new data and a generative AI model optimizes the schedule for the next day.

[2068] Step 14:

[2069] server

[2070] The optimized schedule is sent to the device again.

[2071] Step 15:

[2072] Terminal

[2073] The device will notify parents of the new schedule.

[2074] Step 16:

[2075] User

[2076] Parents input text and voice information about their daily situations and stresses into the app, and biometric information (e.g., heart rate, facial expressions, etc.) is automatically sent to the emotion engine.

[2077] Step 17:

[2078] Terminal

[2079] The device transmits the input text, voice, and biometric information to the server.

[2080] Step 18:

[2081] server

[2082] The server uses an emotion engine to analyze the parent's emotional state from the received data, determining whether the parent is stressed or relieved, for example.

[2083] Step 19:

[2084] server

[2085] Based on the results of the emotion engine, the generative AI model generates a message that best matches the parent's emotions. For example, if the parent is tired, it generates a message such as, "Thank you for your hard work today. It's important to take a short rest."

[2086] Step 20:

[2087] server

[2088] Send the generated message to the terminal.

[2089] Step 21:

[2090] Terminal

[2091] The device notifies the parent of the message, who then views the message.

[2092] Step 22:

[2093] User

[2094] Parents can schedule a private consultation with a specialist using the options within the app, inputting the desired date and time and the content of the consultation.

[2095] Step 23:

[2096] Terminal

[2097] The terminal transmits the reservation information to the server.

[2098] Step 24:

[2099] server

[2100] The server notifies the specialist of the reservation information and obtains confirmation.

[2101] Step 25:

[2102] Expert

[2103] Experts will interact with parents online at designated times and provide personalized advice.

[2104] Step 26:

[2105] User

[2106] Parents can consult with an expert through the app at a designated time and receive necessary advice.

[2107] This means that AI Nentore not only manages babies' sleep, but also provides psychological support to parents, making it a comprehensive sleep support system.

[2108] Example 2

[2109] 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."

[2110] In today's world, it is extremely difficult for parents to properly manage their baby's sleep and maintain an optimal sleep schedule. New parents, in particular, often experience stress due to a lack of knowledge about their baby's sleep patterns, which prevents them from responding appropriately. Furthermore, parents often ignore their own emotional state, which increases parenting stress. Another problem is the lack of easy access to individual consultations with specialists.

[2111] 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.

[2112] In this invention, the server includes input means for parents to input their baby's sleep data, analysis means for receiving and analyzing the data input from the input means, and schedule generation means for generating an optimal sleep schedule for the baby based on the data analyzed by the analysis means, according to the baby's age and developmental stage. This allows parents to appropriately manage their baby's sleep status and maintain an optimal sleep schedule.

[2113] The "input means" is an interface that allows parents to input their baby's sleep data and basic information.

[2114] The "analysis means" is a system for analyzing the data received from the input means and identifying the baby's sleep patterns.

[2115] The "schedule generation means" is a system for generating an optimal sleep schedule according to the baby's age and developmental stage based on the data obtained by the analysis means.

[2116] The "notification means" is a system for notifying parents of the generated sleep schedule so that the parents can be aware of the schedule.

[2117] The "schedule adjustment tool" is a system for correcting and adjusting existing sleep schedules based on new sleep data entered by parents.

[2118] The "message generating means" is a system for providing psychological support messages to parents.

[2119] The "emotion engine means" is a system for analyzing input text, voice, and biometric information to identify the parent's emotional state.

[2120] The "emotion message generating means" is a system for generating an appropriate message based on the parent's emotional state identified by the emotion engine means.

[2121] The "consultation reservation means" is a system that allows parents to make reservations for individual consultations with specialists.

[2122] This invention is a comprehensive childcare support system that combines a system that analyzes and generates an optimal sleep schedule based on the input of a parent's baby's sleep data, with an emotion engine that recognizes the user's emotions. This system aims to not only optimize a baby's sleep environment, but also to reduce the psychological burden on parents.

[2123] Enter your baby's basic information and sleep data

[2124] User

[2125] Parents first enter their baby's basic information (name, age, gender, etc.) into the app, then enter their daily sleep data (wake-up time, bedtime, nap time, frequency of nighttime crying, etc.).

[2126] Terminal

[2127] The terminal transmits the input data to the server. For example, a device equipped with a user interface, such as a smartphone or tablet, is used.

[2128] server

[2129] The server stores the received data in a database (e.g., MySQL, PostgreSQL, etc.). The stored data undergoes initial analysis using analytical tools. For example, analytical software such as Python or R can be used.

[2130] Generation and presentation of optimal sleep schedule

[2131] server

[2132] The server uses a generative AI model (e.g., OpenAI GPT-3) based on the analyzed data to generate an optimal sleep schedule for the baby based on their age and developmental stage. This schedule includes bedtime and nap times. The generated schedule is then sent to the device.

[2133] Terminal

[2134] The device will notify parents of the generated sleep schedule via a pop-up message or alert.

[2135] Schedule adjustments

[2136] User

[2137] Parents re-enter new sleep data, including whether the sleep plan was met and the actual sleep duration.

[2138] Terminal

[2139] The terminal transmits the newly entered data to the server.

[2140] server

[2141] The server will automatically adjust the schedule based on the new data, and the next suggested schedule will be revised to something like "Go to bed at 8 PM, take 1.5 hour naps at 10 AM and 2 PM."

[2142] Providing psychological support

[2143] server

[2144] The server uses a generative AI model to automatically generate encouragement and advice that is sensitive to the parent's feelings. For example, the day after a night of heavy crying, it might generate a message like, "Today was tough, but this is part of growing up. You're a great mom."

[2145] Terminal

[2146] The device notifies the parent of this automatically generated message.

[2147] Individual consultation with an expert

[2148] User

[2149] Within the app, parents select the option to book a private consultation with a specialist and enter the desired date and time and the details of the consultation.

[2150] Terminal

[2151] The terminal transmits the reservation information to the server.

[2152] server

[2153] The server notifies the specialist of the reservation information and obtains confirmation.

[2154] Expert

[2155] Experts will interact with parents online at designated times and provide personalized advice.

[2156] Recognizing user emotions with an emotion engine

[2157] Terminal

[2158] The text, voice data, and even biometric information (e.g., heart rate, facial expressions, etc.) that parents enter into the app are sent to the emotion engine.

[2159] server

[2160] The server's emotion engine analyzes this data and identifies the parent's emotional state, for example, by analyzing emotions such as "stress" or "fatigue" from the text data.

[2161] Emotion-based message generation

[2162] server

[2163] Based on the analysis results of the emotion engine, the generative AI model generates a message appropriate to that emotion. For example, if a parent is tired, it might generate a message such as, "Thank you for your hard work today. It's important to take a short rest."

[2164] Terminal

[2165] The generated message is sent to the device and notified to the parent, allowing the parent to receive support appropriate to the child's emotions at that time.

[2166] Specific examples

[2167] Example 1: Initial Setup and Data Entry

[2168] User: Downloads and launches the app, then enters the baby's name as "Taro," its age as "6 months," and its gender as "male."

[2169] Terminal: Sends the entered information to the server.

[2170] Server: Receives the information, stores it in a database, and begins initial analysis.

[2171] Example 2: Schedule Generation

[2172] User: Enter sleep data (e.g., went to bed at 7pm, cried twice at night, woke up at 6am, took one hour nap at 10am and one hour nap at 2pm).

[2173] Terminal: Sends the entered data to the server.

[2174] Server: Analyzes the data using a generative AI model and generates the next schedule, suggesting "Go to bed at 8pm, take 1 hour and 30 minute naps at 10am and 2pm."

[2175] Example 3: Psychological support through an emotional engine

[2176] User: Texts "I'm so tired because my baby is crying at night."

[2177] Terminal: Sends the entered text data to the emotion engine on the server.

[2178] Server: The emotion engine analyzes the text and identifies that the parent is tired. The generative AI model generates a message such as, "Today was tough. It's important to take some rest."

[2179] Device: Notify parent of message.

[2180] The system will be able to optimize a baby's sleep schedule and provide support tailored to the parent's psychological state through an emotion engine.

[2181] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2182] Step 1:

[2183] User

[2184] Parents download and install the app, then launch it and enter basic information about their baby (such as name, age, and gender), and then enter their baby's daily sleep data (for example, wake-up time, bedtime, nap time, and frequency of nighttime crying).

[2185] Terminal

[2186] The device sends the basic information and sleep data of the baby entered by the parent to the server in real time.

[2187] server

[2188] The server stores the received data in a database, which can be a database management system such as MySQL or PostgreSQL, and then prepares the data for initial analysis.

[2189] Step 2:

[2190] server

[2191] The server analyzes the stored data using an analytical tool, which may be data analysis software such as Python or R. The results of the analysis identify the baby's basic sleep patterns.

[2192] Input: Parent-entered baby information and sleep data

[2193] Output: Analysis of baby's sleep patterns

[2194] Step 3:

[2195] server

[2196] Based on the analysis results, the server uses a generative AI model (e.g., OpenAI GPT-3) to generate an optimal sleep schedule based on the baby's age and developmental stage, including bedtime and nap times.

[2197] Input: Analysis of baby's sleep patterns

[2198] Output: Optimal sleep schedule

[2199] Next, this generated schedule is transmitted to the terminal.

[2200] Step 4:

[2201] Terminal

[2202] The device will notify parents of the optimal sleep schedule sent from the server via pop-up messages and alerts.

[2203] User

[2204] Parents can check the notifications and use the generated sleep schedule to put their baby to bed or adjust nap times.

[2205] Enter: your optimal sleep schedule.

[2206] Output: Parental sleep schedule enforcement

[2207] Step 5:

[2208] User

[2209] Parents then enter the new sleep data into the app again, including details about whether the child was able to sleep as planned and the actual hours of sleep.

[2210] Terminal

[2211] The device sends new sleep data to the server, also in real time.

[2212] Input: New sleep data

[2213] Output: Send new sleep data

[2214] Step 6:

[2215] server

[2216] The server reanalyzes the schedule based on the newly sent sleep data and automatically adjusts it, generating and suggesting a more optimal sleep pattern for the next time.

[2217] Input: New sleep data

[2218] Output: Corrected sleep schedule

[2219] Step 7:

[2220] server

[2221] The server uses an emotion engine to understand the parent's feelings. The parent inputs text, voice data, and biometric information (e.g., heart rate, facial expression, etc.), and based on this, the parent's emotional state is identified.

[2222] Input: text, voice data, biometric information

[2223] Output: Parent's emotional state

[2224] Step 8:

[2225] server

[2226] Based on the parent's emotional state identified by the emotion engine, the generative AI model generates an appropriate message of encouragement or advice, such as, "Today was tough. It's important to take some rest."

[2227] Input: Parent emotional state

[2228] Output: An appropriate message of encouragement or advice

[2229] Step 9:

[2230] Terminal

[2231] The device will notify the parent of the generated message via a push notification or a pop-up message.

[2232] Input: A suitable message of encouragement or advice

[2233] Output: Message notification to parent

[2234] Step 10:

[2235] User

[2236] Parents can use the in-app options to schedule a private consultation with a specialist, inputting the desired topic, date and time.

[2237] Terminal

[2238] The terminal transmits the input reservation information to the server.

[2239] Input: Reservation information (consultation details, date and time)

[2240] Output: Send reservation information

[2241] Step 11:

[2242] server

[2243] The server forwards the received reservation information to the specialist and obtains confirmation of the reservation.

[2244] Input: Reservation information

[2245] Output: Coordination and confirmation with experts

[2246] Step 12:

[2247] Expert

[2248] The expert will then speak to the parent online at a confirmed date and time to provide personalized advice.

[2249] Input: Consultation received from parent

[2250] Output: Personalized advice from an expert

[2251] Through these steps, the system optimizes the baby's sleep schedule, provides support tailored to the parent's psychological state through an emotion engine, and offers expert consultations for more specific advice.

[2252] (Application example 2)

[2253] 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."

[2254] Conventional baby sleep management systems are limited to collecting and analyzing baby sleep data, and lack elements to reduce the psychological burden on parents. Furthermore, they do not provide support that takes into account the parents' emotional and stress states, making it difficult for them to maintain their mental stability. Therefore, there is a need for a more comprehensive support system that can also respond to parents' emotional states.

[2255] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2256] In this invention, the server includes input means for a parent to input sleep data of the child, analysis means for receiving and analyzing the data input from the input means, schedule generation means for generating an optimal sleep schedule according to the child's age and developmental stage based on the data analyzed by the analysis means, notification means for notifying the parent of the sleep schedule generated by the schedule generation means, schedule adjustment means for modifying or adjusting the schedule based on the new sleep data input by the parent, message generation means for providing psychological support messages to the parent, emotion analysis means for receiving and analyzing emotional data of the parent, emotion-based message generation means for generating appropriate support messages for the parent based on the emotional data analyzed by the emotion analysis means, and consultation reservation means for individual consultation with a specialist. This enables not only the optimization of the baby's sleep schedule but also support according to the parent's psychological state.

[2257] The "input means" is an interface that allows parents to input their child's sleep data and emotional state.

[2258] The "analysis means" is a means having a function of analyzing data received from the input means.

[2259] The "schedule generating means" is a means for generating an optimal sleep schedule according to the child's age and stage of development based on the data analyzed by the analyzing means.

[2260] The "notification means" is a means for notifying parents of the generated sleep schedule.

[2261] The "schedule adjustment tool" is a tool for correcting and adjusting the schedule based on new sleep data entered by the parent.

[2262] The "message generating means" is a means for providing psychological support messages to parents.

[2263] The "emotion analysis means" is a means for receiving the parent's emotion data and analyzing the parent's emotional state.

[2264] The "emotion-based message generating means" is a means for generating an appropriate support message for the parent based on the emotion data analyzed by the emotion analyzing means.

[2265] The "consultation reservation means" is a means for making a reservation for individual consultation with a specialist.

[2266] A "generative artificial intelligence model" is a machine learning model that generates optimal schedules and messages based on input data.

[2267] The present invention provides a system that analyzes a child's sleep data entered by a parent and generates and modifies an optimal sleep schedule, as well as a system that recognizes the parent's emotions and provides support messages in response to those emotions. Specific embodiments for implementing this system are described below.

[2268] Hardware and Software

[2269] Hardware:

[2270] Smartphone: Used by parents to enter data and receive notifications from the system.

[2271] Server: The central component responsible for receiving and analyzing data, generating sleep schedules, and sentiment analysis.

[2272] software:

[2273] Python 3.x: Used to implement system-wide programs.

[2274] GUI library (Tkinter): Used to build a user interface for the parent to input data.

[2275] Machine learning libraries: Used to perform data analysis, schedule generation, and emotion recognition using generative AI models.

[2276] System configuration

[2277] 1. Input method:

[2278] Parents use their smartphones to input information such as their child's sleep time, wake-up time, nap time, frequency of night crying, and emotional state into a user interface.

[2279] 2. Analysis method:

[2280] The server analyzes the data received from the input means to identify the child's sleep patterns, using a generative AI model for highly accurate analysis.

[2281] 3. Schedule generation method:

[2282] The server generates an optimal sleep schedule based on the child's age and developmental stage using a generative AI model, and the generated schedule is sent to the smartphone.

[2283] 4. Means of notification:

[2284] The generated sleep schedule is sent to parents' smartphones, helping them put their children to bed at realistic times.

[2285] 5. Scheduling methods:

[2286] When parents enter new sleep data, the server automatically adjusts the schedule based on that data and provides the optimal schedule again.

[2287] 6. Message Generation Method:

[2288] The server uses the generative AI model to provide parents with psychological support messages, such as "Today was tough, but it's part of growing up. You're a great mom" the day after a night of heavy crying.

[2289] 7. Emotion analysis means:

[2290] The system analyzes parental input, including text, voice, and biometric information (heart rate, facial expressions, etc.) to identify the child's emotional state. Emotion analysis is also performed using a generative AI model.

[2291] 8. Emotion-based message generation method:

[2292] Based on the results of emotion analysis, a support message is generated. For example, if the system detects that a parent is "tired," it generates a message such as "Thank you for your hard work today. It's important to take a short rest."

[2293] 9. How to book a consultation:

[2294] It provides a user interface for parents to book individual consultations with specialists. The booking information is sent to the server and confirmed and approved by the specialist.

[2295] Specific examples

[2296] Example 1: Initial Setup and Data Entry

[2297] The parent downloads and launches the app, entering the child's name as "Taro," age as "6 months," and gender as "male."

[2298] The smartphone sends the entered information to the server, which stores the received information in a database and begins initial analysis.

[2299] Example 2: Schedule Generation

[2300] Parents enter sleep data (e.g., baby goes to bed at 7pm, cries twice at night, wakes up at 6am, takes one-hour naps at 10am and 2pm).

[2301] The smartphone sends the input data to the server, which then analyzes it using a generative AI model to generate the next schedule.

[2302] The generated schedule suggests "go to bed at 8pm, take 1 hour and 30 minute naps at 10am and 2pm."

[2303] Example 3: Psychological support through an emotional engine

[2304] A parent texts, "I'm so tired because my baby is crying at night."

[2305] The smartphone sends the entered text data to the server's emotion engine, which analyzes the text and determines that the parent is tired.

[2306] The generative AI model generates messages such as, "Today was tough. It's important to take some rest."

[2307] A message is sent to the smartphone, and parents can receive psychological support.

[2308] Example prompt sentence:

[2309] Please enter your baby's basic information. Name: "Taro", Age: "6 months", Gender: Do not enter

[2310] Next, enter your baby's sleep data: Wake-up time: "06:00", Bedtime: "20:00", Nap time: "2 times, 1 hour each", Night crying: "2 times"

[2311] Enter your emotion. Emotion: "I'm tired."

[2312] In this manner, the present invention can optimize the baby's sleep schedule as well as provide support according to the parent's emotional state, thereby comprehensively supporting the sleep environment for both parent and baby.

[2313] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2314] Step 1:

[2315] Parents enter basic information about their children.

[2316] How it works: The user (parent) uses the smartphone's user interface to enter basic information about their child, such as their name, age, and gender.

[2317] Input: Name, age, gender

[2318] Output: Basic information data

[2319] Data processing: The basic information entered is sent from the smartphone to the server.

[2320] Step 2:

[2321] An initial analysis is performed based on basic information.

[2322] Operation: The server stores the received basic information in a database and begins initial analysis. Based on the analysis results, it prepares for initial configuration.

[2323] Input: Basic information data

[2324] Output: Analysis result data

[2325] Data calculation: Analyze basic information and generate basic analysis results according to the child's age.

[2326] Step 3:

[2327] Parents enter their child's sleep data.

[2328] Operation: The user (parent) uses the smartphone's user interface to input their child's sleep data (e.g., wake-up time, bedtime, nap time, frequency of night crying, etc.).

[2329] Input: Sleep data (wake-up time, bedtime, nap time, frequency of night crying)

[2330] Output: Sleep data

[2331] Data processing: The entered sleep data is sent from the smartphone to the server.

[2332] Step 4:

[2333] Analyzes sleep data and generates an optimal sleep schedule.

[2334] How it works: The server analyzes the input sleep data using a generative AI model and generates an optimal sleep schedule based on the child's age and developmental stage.

[2335] Input: Sleep data

[2336] Output: Optimal sleep schedule

[2337] Data Computing: Generative AI models are used to analyze data and generate schedules.

[2338] Step 5:

[2339] The generated sleep schedule is notified to the parent.

[2340] How it works: The server notifies the smartphone of the generated optimal sleep schedule, and the user (parent) receives the notification.

[2341] Enter: optimal sleep schedule

[2342] Output: Notification message

[2343] Data processing: The generated schedule is processed into a notification message and sent to the smartphone.

[2344] Step 6:

[2345] Parents enter new sleep data and reschedule.

[2346] How it works: The user (parent) re-enters sleep data, and the server automatically readjusts the schedule based on that data.

[2347] Input: New sleep data

[2348] Output: A recalibrated optimal sleep schedule

[2349] Data calculations: Recalculate the schedule based on new data using generative AI models.

[2350] Step 7:

[2351] Parental emotional data is input and the emotional state is analyzed.

[2352] Operation: The user (parent) inputs emotional data (text, voice, biometric information, etc.) using the smartphone's user interface. The server analyzes the emotional data using emotion analysis means and identifies the parent's emotional state.

[2353] Input: Emotion data

[2354] Output: Emotion analysis results

[2355] Data processing: The emotional data is analyzed using emotion analysis means to identify the emotional state of the parents.

[2356] Step 8:

[2357] A support message based on the results of emotion analysis is generated and notified to the parent.

[2358] How it works: Based on the results of emotion analysis, the server uses a generative AI model to generate an appropriate support message for the parent. The generated message is then sent to the smartphone.

[2359] Input: Sentiment analysis results

[2360] Output: Support message

[2361] Data calculation: Based on the results of sentiment analysis, a generative AI model generates support messages.

[2362] Step 9:

[2363] Book a private consultation with an expert.

[2364] Operation: The user (parent) makes an appointment with a specialist using the user interface on their smartphone. The appointment information is sent to the server and notified to the specialist.

[2365] Input: Reservation information (desired date and time, consultation details, etc.)

[2366] Output: Reservation confirmation message

[2367] Data processing: The reservation information is sent to the server and notified to the specialist.

[2368] 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.

[2369] 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.

[2370] 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.

[2371] [Fourth embodiment]

[2372] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[2373] 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.

[2374] 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).

[2375] 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.

[2376] 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.

[2377] 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).

[2378] 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.

[2379] 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.

[2380] 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.

[2381] 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.

[2382] 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.

[2383] 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.

[2384] 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."

[2385] This invention is a system that automatically generates and modifies an optimal sleep schedule based on the analysis of sleep data entered by parents. The purpose of this system is to provide comprehensive support for the sleep environment of parents and babies.

[2386] Program processing overview

[2387] Enter your baby's basic information and sleep data

[2388] User

[2389] Parents first enter their baby's basic information (name, age, gender, etc.) into the app, then enter their daily sleep data (wake-up time, bedtime, nap time, frequency of nighttime crying, etc.).

[2390] Terminal

[2391] The terminal transmits the input data to the server.

[2392] server

[2393] The server stores the received data in a database and analyzes it to identify the baby's sleep patterns.

[2394] Generation and presentation of optimal sleep schedule

[2395] server

[2396] The server then generates an optimal sleep schedule for the baby based on the baby's sleep patterns, including bedtime and daytime naps, and sends the schedule to the device.

[2397] Terminal

[2398] The device will then notify the parents of the generated sleep schedule, allowing them to get their baby to sleep based on this schedule.

[2399] Schedule adjustments

[2400] User

[2401] Parents will then re-enter any new sleep data their baby actually had, including whether they slept as planned and the actual hours of sleep.

[2402] Terminal

[2403] The terminal transmits the newly entered data to the server.

[2404] server

[2405] The server automatically adjusts the schedule based on the new data it receives, so that the next time it suggests a schedule that better suits your baby's sleep patterns.

[2406] Providing psychological support

[2407] server

[2408] To ease the psychological burden on parents, the server uses a generative AI model to automatically generate encouraging messages and advice. For example, the server might generate a message the day after a night of heavy crying, such as, "Today was tough, but it's part of growing up. You're a great mom."

[2409] Terminal

[2410] The device will then notify the parent of this automatically generated message, allowing the parent to receive psychological support.

[2411] Individual consultation with an expert

[2412] User

[2413] Parents can schedule a private consultation with a specialist within the app. For example, they can press the "Book a consultation" button and enter the desired date and time and the content of the consultation.

[2414] Terminal

[2415] The terminal transmits the reservation information to the server.

[2416] server

[2417] The server notifies the specialist of the reservation information and obtains confirmation.

[2418] Expert

[2419] Experts will interact with parents online at designated times and provide personalized advice.

[2420] Specific examples

[2421] Example 1: Initial Setup and Data Entry

[2422] User: Downloads and launches the app, then enters the baby's name as "Taro," age as "6 months," and gender as "male."

[2423] Terminal: Sends the entered information to the server.

[2424] Server: Receives information, stores it in a database, and begins initial analysis.

[2425] Example 2: Schedule Generation

[2426] User: Enter sleep data (e.g., went to bed at 7pm, cried twice at night, woke up at 6am, took one hour nap at 10am and one hour nap at 2pm).

[2427] Terminal: Sends entered data to the server.

[2428] Server: Analyzes the data using a generative AI model and generates the next schedule, suggesting "go to bed at 8pm, take 1 hour and 30 minute naps at 10am and 2pm."

[2429] Example 3: Providing psychological support messages

[2430] Server: After a series of nights of constant crying, the server automatically generates a message like, "Today was tough, but don't worry, it's part of growing up."

[2431] Device: Notifies parents of messages, giving them peace of mind.

[2432] This system allows parents to properly manage their baby's sleep and create an optimal sleeping environment with the help of expert advice. It also contributes to reducing stress for parents through psychological support. In this way, the present invention can improve the quality of sleep for both parents and babies.

[2433] The processing flow will be explained below.

[2434] Step 1:

[2435] User

[2436] Parents download the app and enter basic information about their baby (such as name, age, and gender) when they first launch it.

[2437] Step 2:

[2438] Terminal

[2439] The terminal transmits the input basic information to the server.

[2440] Step 3:

[2441] server

[2442] The server stores the received basic information about the baby in a database and prepares it for analysis.

[2443] Step 4:

[2444] User

[2445] Parents enter sleep data from the past 24 hours (wake-up time, bedtime, nap time, frequency of nighttime crying, etc.) into the app.

[2446] Step 5:

[2447] Terminal

[2448] The terminal transmits the input sleep data to the server.

[2449] Step 6:

[2450] server

[2451] The server analyzes the received sleep data to identify the baby's sleep patterns, which are then used to further analyze the data using a generative AI model.

[2452] Step 7:

[2453] server

[2454] The server uses a generative AI model to generate an optimal sleep schedule for the baby based on their age and developmental stage, including nighttime bedtime and daytime nap times.

[2455] Step 8:

[2456] server

[2457] The generated sleep schedule is sent to the device.

[2458] Step 9:

[2459] Terminal

[2460] The device will then notify the parent of the received sleep schedule, which the parent can then view on the app.

[2461] Step 10:

[2462] User

[2463] Parents can put their babies to sleep based on the schedule they are notified of.

[2464] Step 11:

[2465] User

[2466] Parents will then again enter the actual sleep performance for that day (e.g., whether they went to bed as planned, how long they slept, etc.) into the app.

[2467] Step 12:

[2468] Terminal

[2469] The terminal transmits the newly input sleep performance data to the server.

[2470] Step 13:

[2471] server

[2472] The server analyzes the new data and uses a generative AI model to optimize the schedule for the next day.

[2473] Step 14:

[2474] server

[2475] The new optimized schedule is sent to the device.

[2476] Step 15:

[2477] Terminal

[2478] The device will notify the parent of the new schedule and allow them to run it again.

[2479] Step 16:

[2480] server

[2481] The server uses a generative AI model to automatically generate messages aimed at providing psychological support to parents, including encouragement and advice.

[2482] Step 17:

[2483] server

[2484] Send the generated message to the terminal.

[2485] Step 18:

[2486] Terminal

[2487] The device will notify the parent of the message, who can then view it.

[2488] Step 19:

[2489] User

[2490] Parents select the option within the app to schedule a private consultation with a specialist, inputting the desired date and time and the details of the consultation.

[2491] Step 20:

[2492] Terminal

[2493] The terminal transmits the reservation information to the server.

[2494] Step 21:

[2495] server

[2496] The server notifies the specialist of the reservation information and obtains confirmation.

[2497] Step 22:

[2498] Expert

[2499] Experts will interact with parents online at designated times and provide personalized advice.

[2500] Step 23:

[2501] User

[2502] Parents can consult with an expert through the app at a designated time and receive necessary advice.

[2503] These steps guide the system through a series of processes to improve the baby's sleep quality and reduce stress for parents.

[2504] Example 1

[2505] 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."

[2506] Babies' sleep patterns vary greatly from baby to baby, making it extremely difficult for parents to establish an appropriate sleep schedule. As a result, parents often spend a lot of time and effort managing their baby's sleep, and become stressed. Furthermore, to receive specialized advice tailored to the baby's developmental stage, individual consultations with specialists are required, which is also time-consuming. Traditional methods make it difficult to comprehensively resolve these issues.

[2507] 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.

[2508] In this invention, the server includes an input means for a parent to input their baby's sleep data, an analysis means for receiving and analyzing the data input from the input means, a schedule generation means for generating an optimal sleep schedule based on the baby's age and developmental stage based on the data analyzed by the analysis means, a notification means for notifying the parent of the sleep schedule generated by the schedule generation means, a schedule adjustment means for modifying or adjusting the schedule based on the new sleep data input by the parent, a message generation means for providing psychological support messages to the parent, a consultation reservation means for individual consultations with a specialist, a transmission means for transmitting the data input from the input means to the server, a storage means for the server to store the baby's sleep data in a database, and a means for the analysis means to analyze the sleep patterns using a generative artificial intelligence model. This allows parents to automatically generate or modify an optimal sleep schedule based on their baby's individual sleep patterns and support their baby's development through psychological support messages and individual consultations with a specialist.

[2509] 1. "Input means" refers to a device or interface that allows parents to input their baby's sleep data.

[2510] 2. "Analysis means" refers to the device or algorithm used to analyze the input data and identify the baby's sleep patterns.

[2511] 3. "Schedule generation means" refers to a device or algorithm that creates an optimal sleep schedule based on the baby's age and developmental stage based on analyzed data.

[2512] 4. "Notification means" refers to a device or system that notifies parents of the generated sleep schedule.

[2513] 5. "Schedule Adjustment Tool" means a device or algorithm that modifies or adjusts a sleep schedule based on new sleep data entered by a parent.

[2514] 6. "Message generation means" refers to a device or system for generating and providing psychological support messages to parents.

[2515] 7. "Consultation booking means" refers to a device or system for booking an individual consultation with a specialist.

[2516] 8. "Transmission means" refers to a device or system for transmitting data entered through the input means to the server.

[2517] 9. "Storage means" refers to the device or system that allows the server to store the baby's sleep data in a database.

[2518] 10. "Generative AI model" refers to a machine learning algorithm that analyzes input data to understand and predict a baby's sleep patterns.

[2519] The present invention is a system that allows parents to input their baby's sleep data, analyzes the data, and automatically generates and modifies an optimal sleep schedule. The purpose of this system is to provide comprehensive support for the sleep environment of parents and babies. The following describes an embodiment of this system.

[2520] Enter your baby's basic information and sleep data

[2521] User

[2522] Parents use a smartphone app to enter basic information about their baby (such as name, age in months, and gender). The user then uses the app's input form to enter data, providing information such as the baby's name as "Taro," its age as "6 months," and its gender as "male." The parent then enters daily sleep data (such as wake-up time, bedtime, nap time, and frequency of nighttime crying) in the same way.

[2523] Sending input data

[2524] Terminal

[2525] The terminal organizes the data entered by the user and sends it to the server using a secure communication protocol (e.g. HTTPS). All entered data is encrypted and securely transferred to the server.

[2526] Data storage and analysis

[2527] server

[2528] The server stores the received user data in a database (e.g., MySQL). The stored data is indexed and organized for efficient search and analysis. The server then uses data analysis software, such as Python scripts, to analyze the sleep data and identify the baby's sleep patterns. Generative artificial intelligence models (generative AI models) are used in the analysis to improve the accuracy of data processing.

[2529] Generating an optimal sleep schedule

[2530] server

[2531] The server generates an optimal sleep schedule based on the identified baby's sleep patterns and developmental stage. A generative AI model (e.g., a model using TensorFlow) is used for generation. The model receives a prompt: "Please suggest a new sleep schedule based on the current sleep patterns of a 6-month-old baby." The server generates a new schedule as a prediction.

[2532] Schedule Notifications

[2533] Terminal

[2534] The device then notifies the parent of the optimal sleep schedule received from the server. The schedule is displayed on the parent's smartphone using the push notification function. For example, a specific schedule such as "Go to bed at 8 p.m., take 1.5 hour naps at 10 a.m. and 2 p.m." may be displayed.

[2535] Entering new sleep data

[2536] User

[2537] Parents then enter their baby's new sleep data into the app again, using a dedicated form in the app to record the actual number of hours of sleep, the number of nighttime crying episodes, and the length of naps in detail.

[2538] Rescheduling

[2539] Terminal

[2540] The device then sends the newly entered sleep data to the server, again via a secure communications protocol.

[2541] server

[2542] The server re-analyzes the current sleep schedule based on the new data received and automatically adjusts the schedule as needed, using machine learning algorithms to update the schedule based on the baby's latest sleep patterns.

[2543] Generating psychological support messages

[2544] server

[2545] The server automatically generates an encouraging message using a generative AI model (e.g., GPT-3) to provide psychological support to parents. An example of a prompt is "Please create an encouraging message for a parent whose child is crying a lot at night.", and generates an encouraging message for the parent.

[2546] Message notifications

[2547] Terminal

[2548] The device will then notify the parent of the generated encouraging message via an in-app message box or push notification, so the parent can see it immediately.

[2549] Book a private consultation with an expert

[2550] User

[2551] Parents press the "Book a consultation" button in the app and enter the desired date and time and the content of the consultation.

[2552] Terminal

[2553] The terminal transmits the reservation information input by the user to the server.

[2554] server

[2555] The server notifies the relevant specialist of the received reservation information, and the specialist prepares to interact with the parent online at the specified time and provide individual advice.

[2556] In this way, the present invention can provide a concrete means for improving the quality of sleep for parents and their babies, allowing parents to effectively manage their babies' sleep and reduce stress.

[2557] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2558] Step 1:

[2559] User

[2560] Parents launch the smartphone app and enter basic information about their baby (such as name, age in months, and gender). The data is entered in the format of "baby's name," "age in months," and "gender." Based on this, the app stores the information entered in the fields in an internal data structure.

[2561] Input: Baby's basic information (e.g. name, age, sex)

[2562] Output: Basic information stored in the app's internal data structures

[2563] Step 2:

[2564] Terminal

[2565] The terminal organizes the data entered by the user and sends it to the server using a secure communication protocol (e.g., HTTPS). The data for each field is serialized in JSON format or similar and sent to the server in encrypted form.

[2566] Input: Basic baby information

[2567] Output: Basic information sent to the server

[2568] Step 3:

[2569] server

[2570] The server stores the received user data in a database (e.g., MySQL), which is then indexed using a database management system and prepared for efficient later searching and analysis.

[2571] Input: Baby data sent from the device

[2572] Output: Baby data stored in a database

[2573] Step 4:

[2574] User

[2575] Parents enter daily sleep data (wake-up time, bedtime, nap time, nighttime crying frequency, etc.) into the app. As data is entered into input fields, the app stores it in an internal data structure.

[2576] Input: Sleep data (e.g., wake-up time, bedtime, nap time, frequency of night crying)

[2577] Output: Sleep data stored in the app's internal data structure

[2578] Step 5:

[2579] Terminal

[2580] The device organizes the sleep data entered by the user and sends it to the server using a secure communication protocol (e.g., HTTPS). The data is serialized in JSON format, encrypted, and sent to the server.

[2581] Input: Sleep data

[2582] Output: Sleep data sent to the server

[2583] Step 6:

[2584] server

[2585] The server stores the received sleep data in a database. It also analyzes the sleep data using analysis software such as Python scripts. A generative AI model is used for the analysis to identify the baby's sleep patterns. For example, the prompt sentence is "Based on the baby's sleep data, please identify the sleep patterns."

[2586] Input: Sleep data

[2587] Data processing / calculation: Analysis using generative AI models

[2588] Output: Identified sleep patterns

[2589] Step 7:

[2590] server

[2591] The server uses a generative AI model to generate an optimal sleep schedule based on the identified sleep patterns and age. The server generates a new schedule using the prompt, "Please suggest a new sleep schedule based on the current sleep patterns of a 6-month-old baby."

[2592] Input: Identified sleep pattern, age in months

[2593] Data processing / calculation: Schedule generation using generative AI models

[2594] Output: Optimal sleep schedule

[2595] Step 8:

[2596] Terminal

[2597] The device notifies the user of the optimal sleep schedule received from the server, and the schedule is displayed on the parent's smartphone using the push notification function.

[2598] Enter: your optimal sleep schedule.

[2599] Output: Sleep schedule notified to parent

[2600] Step 9:

[2601] User

[2602] The parent re-enters the new sleep data into the app, which updates the app's internal data structures.

[2603] Input: New sleep data

[2604] Output: New sleep data stored in the app's internal data structure.

[2605] Step 10:

[2606] Terminal

[2607] The device then sends the newly entered data to the server, again via a secure communications protocol.

[2608] Input: New sleep data

[2609] Output: New sleep data sent to the server.

[2610] Step 11:

[2611] server

[2612] The server reanalyzes the current schedule based on the new data received and automatically adjusts the schedule. Machine learning algorithms are used to update the optimal schedule based on the new data.

[2613] Input: New sleep data

[2614] Data processing / calculation: Reanalysis using machine learning algorithms

[2615] Output: Adjusted schedule

[2616] Step 12:

[2617] server

[2618] The server automatically generates encouraging messages using a generative AI model to provide psychological support to parents. The message is generated based on the prompt, "Please create an encouraging message for parents whose child has been crying a lot at night."

[2619] Input: Sleep data, generative AI model

[2620] Data processing / calculation: Message generation using generative AI models

[2621] Output: An encouraging message

[2622] Step 13:

[2623] Terminal

[2624] The device will then notify the parent of the generated encouraging message via a message box within the app or a push notification.

[2625] Input: An encouraging message

[2626] Output: Message sent to parent

[2627] Step 14:

[2628] User

[2629] Parents press the "Book a consultation" button in the app and enter the desired date and time and the content of the consultation.

[2630] Input: Reservation information (desired date and time, consultation details)

[2631] Output: Reservation information stored in the app's internal data structure

[2632] Step 15:

[2633] Terminal

[2634] The terminal transmits the reservation information input by the user to the server.

[2635] Input: Reservation information

[2636] Output: Reservation information sent to the server

[2637] Step 16:

[2638] server

[2639] The server notifies the relevant specialist of the received reservation information and prepares the specialist to interact with the parent online at the specified time.

[2640] Input: Reservation information

[2641] Output: Booking information notified to the expert

[2642] In this way, all the steps work together to form a system that provides a holistic supportive sleep environment for parents and babies.

[2643] (Application example 1)

[2644] 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."

[2645] As autonomous vehicle technology evolves, driver health and sleep management are becoming important issues for accident prevention and safe driving. Drivers driving long distances in particular need to be able to take appropriate breaks and receive immediate warnings when they feel drowsy. However, conventional systems often cannot meet these needs, so there is a need for technology that can accurately grasp the driver's health and psychological burden, and generate and notify optimal break schedules based on that information.

[2646] 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.

[2647] In this invention, the server includes input means for the driver to input sleep data, analysis means for receiving and analyzing the data input from the input means, schedule generation means for generating an optimal rest schedule according to the driver's health state based on the data analyzed by the analysis means, notification means for notifying the driver of the rest schedule generated by the schedule generation means, schedule adjustment means for correcting and adjusting the schedule based on the new sleep data input by the driver, message generation means for providing the driver with a psychological support message, and consultation reservation means for individual consultation with a specialist. This makes it possible to accurately grasp the driver's health state and psychological burden, and to generate and notify the optimal rest schedule and issue immediate warnings based on that information.

[2648] "Driver" means a person who uses or controls an automated vehicle.

[2649] "Sleep data" refers to information entered by the driver, such as the amount of sleep, wake-up time, rest time, and frequency of drowsiness.

[2650] "Input means" means a device or interface through which a driver inputs sleep data.

[2651] The "analysis means" refers to software or hardware for analyzing the sleep data received from the input means.

[2652] The "schedule generation means" is a system that creates an optimal rest schedule according to the driver's health condition based on the data analyzed by the analysis means.

[2653] The "notification means" refers to a device or interface for notifying the driver of the generated rest schedule.

[2654] The "schedule adjustment tool" refers to a system that modifies and adjusts existing schedules based on newly entered sleep data by drivers.

[2655] The "message generating means" refers to a system that generates psychological support messages for the driver.

[2656] A "consultation reservation means" is a device or interface that accepts reservations for individual consultations with experts.

[2657] A "generative AI model" is an artificial intelligence algorithm or system for analyzing data and generating messages.

[2658] This invention is a system for supporting the health and sleep management of drivers of self-driving vehicles, and is realized by the following steps.

[2659] System Overview

[2660] 1. Enter your sleep data

[2661] User: First, the driver installs the app and enters basic information (name, age, gender, etc.), then enters daily sleep data (wake-up time, bedtime, rest time, frequency of drowsiness, etc.).

[2662] Device: Use a device such as a smartphone or head-mounted display to send the input data to the server.

[2663] Server: The server stores the received data in a database (e.g., MySQL).

[2664] 2. Data analysis and schedule generation

[2665] Server: The server uses a generative AI model (such as TensorFlow) to analyze the stored data. The analytical model identifies the driver's health and sleep patterns.

[2666] Server: Based on the analysis results, the schedule generation means generates an optimal break schedule, which includes break timing and recommended break duration.

[2667] 3. Schedule notification and adjustment

[2668] Terminal: The generated rest schedule is communicated to the driver via smart glasses or a head-mounted display.

[2669] User: The driver re-enters new sleep data (e.g., unplanned nap, actual rest time, etc.).

[2670] Terminal: New data entered is sent to the server.

[2671] Server: Based on the new data, the schedule generator automatically adjusts the schedule and applies it next time, providing a more accurate break schedule.

[2672] 4. Real-time warning system

[2673] Server: The analysis means determines the driver's drowsiness in real time.

[2674] Device: When the driver feels drowsy, a warning message is displayed on smart glasses or a head-mounted display.

[2675] 5. Providing psychological support messages

[2676] Server: The server uses a generative AI model to automatically generate encouraging and advice messages, such as "You had a hard time today, but this is part of your growth. You're a great driver."

[2677] Device: This message is sent to the driver via smart glasses or a head-mounted display, allowing the driver to receive psychological support.

[2678] 6. Individual consultation with an expert

[2679] User: Drivers can schedule a private consultation with a sleep specialist within the app by pressing the "Book a Consultation" button and entering the desired date and time and the details of the consultation.

[2680] Terminal: The reservation information is sent to the server.

[2681] Server: The server notifies the expert of the reservation information and gets confirmation.

[2682] Experts: Experts will interact with drivers online at designated times and provide personalized advice.

[2683] Specific examples

[2684] Example prompt sentence:

[2685] User: Enter the driver's name, age, gender, and daily sleep data.

[2686] System: The proposed break time is 14:00. Please take a one-hour break now.

[2687] System: You are feeling drowsy. We recommend you take a break or seek professional advice.

[2688] System: You've had a tough day, but good luck. You're a great driver.

[2689] This system allows drivers to properly manage their health and receive expert advice to create an optimal rest environment. It also helps reduce driver stress through psychological support. This will improve the safety of autonomous vehicles and reduce the risk of accidents.

[2690] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2691] Step 1:

[2692] User: The driver installs the app and enters basic information (name, age, gender, etc.) Once this basic information is entered, the device sends it to the server.

[2693] Input: Driver's name, age, gender

[2694] Output: Send basic information to the server

[2695] Step 2:

[2696] Device: The driver enters their daily sleep data (wake-up time, bedtime, rest time, frequency of drowsiness, etc.) into the app. The device then sends this data to the server.

[2697] Input: Driver sleep duration, wake-up time, rest time, frequency of drowsiness

[2698] Output: Send sleep data to the server

[2699] Step 3:

[2700] Server: The server stores the received basic information and daily sleep data in a database (e.g., MySQL). The stored data is analyzed using a generative AI model (e.g., TensorFlow).

[2701] Input: Basic information and sleep data to the server

[2702] Output: Data storage in database, data analysis using analytical model

[2703] Step 4:

[2704] Server: Based on the data analyzed using the generative AI model, the driver's health condition and sleep patterns are identified. Based on the analysis results, the server generates an optimal rest schedule using a schedule generation tool.

[2705] Input: Analyzed sleep data

[2706] Output: Generate an optimal break schedule

[2707] Step 5:

[2708] Terminal: The generated rest schedule is notified to the driver via smart glasses or a head-mounted display. The schedule information is displayed in real time using the notification method.

[2709] Input: Break schedule from schedule generator

[2710] Output: Notify driver of break schedule

[2711] Step 6:

[2712] User: The driver enters new sleep data (e.g., unplanned naps, actual rest times, etc.) into the device. The device sends the new data to the server.

[2713] Input: New sleep data

[2714] Output: Send new data to the server

[2715] Step 7:

[2716] Server: Based on the new sleep data, the server recalculates and adjusts the existing rest schedule using the schedule adjustment method.

[2717] Input: New sleep data

[2718] Output: Generate an adjusted break schedule

[2719] Step 8:

[2720] Device: The adjusted break schedule is notified to the driver, and the device displays the adjusted schedule in real time.

[2721] Input: Adjusted break schedule

[2722] Output: Notification of adjusted schedule to driver

[2723] Step 9:

[2724] Server: The analysis means determines the driver's drowsiness in real time. If drowsiness is detected, the server immediately generates a warning message.

[2725] Input: Real-time driver status data

[2726] Output: Generate a warning message

[2727] Step 10:

[2728] Device: When a driver feels drowsy, a warning message will appear on the smart glasses or head-mounted display, prompting them to take an immediate break.

[2729] Input: warning message

[2730] Output: Notify driver of warning message

[2731] Step 11:

[2732] Server: The server uses a generative AI model to automatically generate encouraging and advice messages, such as "You had a hard time today, but this is part of your growth. You're a great driver."

[2733] Input: Driver sleep and health data

[2734] Output: Generates encouraging and advice messages

[2735] Step 12:

[2736] Device: The generated psychological support message is sent to the driver via smart glasses or a head-mounted display.

[2737] Input: Support message

[2738] Output: Notify driver of support message

[2739] Step 13:

[2740] Users: Drivers can book a private consultation with a sleep specialist within the app by entering the desired date and time and the details of the consultation.

[2741] Input: Consultation reservation information

[2742] Output: Send reservation information to the server

[2743] Step 14:

[2744] Server: The reservation information is stored on the server and notified to the expert. An online dialogue with the expert is prepared.

[2745] Input: Consultation reservation data

[2746] Output: Expert notification and confirmation

[2747] Step 15:

[2748] Experts: Experts will interact with drivers online at designated times and provide personalized advice.

[2749] Input: Consultation details from the driver, reservation information

[2750] Output: Expert advice

[2751] 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.

[2752] This system combines a system that allows parents to input their baby's sleep data, analyzes it, and generates and modifies an optimal sleep schedule, with an emotion engine that recognizes the user's emotions. The system aims to provide comprehensive support for the sleep environment of parents and babies, and reduce the psychological burden on parents.

[2753] Program processing overview

[2754] Enter your baby's basic information and sleep data

[2755] User

[2756] Parents first enter their baby's basic information (name, age, gender, etc.) into the app, then enter their daily sleep data (wake-up time, bedtime, nap time, frequency of nighttime crying, etc.).

[2757] Terminal

[2758] The terminal transmits the input data to the server.

[2759] server

[2760] The server stores the received data in a database and analyzes the information, which can then be used to identify the baby's sleep patterns.

[2761] Generation and presentation of optimal sleep schedule

[2762] server

[2763] The server uses the generative AI model to generate an optimal sleep schedule for the baby based on their age and developmental stage, including bedtime and daytime naps, and then sends the schedule to the device.

[2764] Terminal

[2765] The device will then notify the parents of the generated sleep schedule, allowing them to get their baby to sleep based on this schedule.

[2766] Schedule adjustments

[2767] User

[2768] Parents will then re-enter any new sleep data their baby actually had, including whether they slept as planned and the actual hours of sleep.

[2769] Terminal

[2770] The terminal transmits the newly entered data to the server.

[2771] server

[2772] The server automatically adjusts the schedule based on the new data, so that the next time it suggests a schedule that better suits your baby's sleep patterns.

[2773] Providing psychological support

[2774] server

[2775] The server uses a generative AI model to automatically generate encouragement and advice that is sensitive to the parent's feelings. For example, the day after a night of heavy crying, the server might generate a message like, "Today was tough, but this is part of growing up. You're a great mom."

[2776] Terminal

[2777] The device will then notify the parent of this automatically generated message, allowing the parent to receive psychological support.

[2778] Individual consultation with an expert

[2779] User

[2780] Parents select the option to book a private consultation with a specialist within the app and enter the desired date and time and the details of the consultation.

[2781] Terminal

[2782] The terminal transmits the reservation information to the server.

[2783] server

[2784] The server notifies the specialist of the reservation information and obtains confirmation.

[2785] Expert

[2786] Experts will interact with parents online at designated times and provide personalized advice.

[2787] Recognizing user emotions with an emotion engine

[2788] Terminal

[2789] The text and voice data that parents enter into the app, as well as biometric information (such as heart rate and facial expressions), are sent to the emotion engine.

[2790] server

[2791] The server's emotion engine analyzes this data to determine the parent's emotional state, whether they are stressed, relieved, or experiencing a specific emotion.

[2792] Emotion-based message generation

[2793] server

[2794] Based on the analysis results of the emotion engine, the generative AI model generates a message that best suits that emotion. For example, if a parent is tired, it will generate a message such as, "Thank you for your hard work today. It's important to take a short rest."

[2795] Terminal

[2796] The generated message is sent to the device and notified to the parent, allowing the parent to receive support appropriate to the child's emotions at that time.

[2797] Specific examples

[2798] Example 1: Initial Setup and Data Entry

[2799] User: Downloads and launches the app, then enters the baby's name as "Taro," age as "6 months," and gender as "male."

[2800] Terminal: Sends the entered information to the server.

[2801] Server: Receives information, stores it in a database, and begins initial analysis.

[2802] Example 2: Schedule Generation

[2803] User: Enter sleep data (e.g., went to bed at 7pm, cried twice at night, woke up at 6am, took one hour nap at 10am and one hour nap at 2pm).

[2804] Terminal: Sends entered data to the server.

[2805] Server: Analyzes the data using a generative AI model and generates the next schedule, suggesting "go to bed at 8pm, take 1 hour and 30 minute naps at 10am and 2pm."

[2806] Example 3: Psychological support through an emotional engine

[2807] User: Texts "I'm so tired because my baby is crying at night."

[2808] Terminal: Sends the entered text data to the emotion engine on the server.

[2809] Server: The emotion engine analyzes the text and identifies that the parent is tired. The generative AI model generates a message such as, "Today was tough. It's important to take some rest."

[2810] Device: Notify parent of message.

[2811] This allows the system to not only optimize the baby's sleep schedule, but also provide support tailored to the parent's psychological state through an emotion engine, reducing stress for the parent.

[2812] The processing flow will be explained below.

[2813] Step 1:

[2814] User

[2815] Parents download the app and enter basic information about their baby (such as name, age, and gender) when they first launch it.

[2816] Step 2:

[2817] Terminal

[2818] The terminal transmits the input basic information to the server.

[2819] Step 3:

[2820] server

[2821] The server stores the received basic information about the baby in a database and prepares it for analysis.

[2822] Step 4:

[2823] User

[2824] Parents enter their child's daily sleep data (wake-up time, bedtime, nap time, frequency of nighttime crying, etc.) into the app.

[2825] Step 5:

[2826] Terminal

[2827] The device transmits the entered sleep data to the server.

[2828] Step 6:

[2829] server

[2830] The server analyzes the received sleep data and identifies the baby's sleep patterns.

[2831] Step 7:

[2832] server

[2833] Based on the analyzed data, the generative AI model generates an optimal sleep schedule based on the baby's age and developmental stage.

[2834] Step 8:

[2835] server

[2836] The generated sleep schedule is sent to the device.

[2837] Step 9:

[2838] Terminal

[2839] The device notifies the parent of the generated sleep schedule.

[2840] Step 10:

[2841] User

[2842] Parents can put their babies to sleep based on the schedule they are notified of.

[2843] Step 11:

[2844] User

[2845] Enter your actual sleep performance for that day (e.g., whether you slept as planned, how long you slept, etc.) into the app again.

[2846] Step 12:

[2847] Terminal

[2848] The terminal transmits the newly input sleep performance data to the server.

[2849] Step 13:

[2850] server

[2851] The server analyzes the new data and a generative AI model optimizes the schedule for the next day.

[2852] Step 14:

[2853] server

[2854] The optimized schedule is sent to the device again.

[2855] Step 15:

[2856] Terminal

[2857] The device will notify parents of the new schedule.

[2858] Step 16:

[2859] User

[2860] Parents input text and voice information about their daily situations and stresses into the app, and biometric information (e.g., heart rate, facial expressions, etc.) is automatically sent to the emotion engine.

[2861] Step 17:

[2862] Terminal

[2863] The device transmits the input text, voice, and biometric information to the server.

[2864] Step 18:

[2865] server

[2866] The server uses an emotion engine to analyze the parent's emotional state from the received data, determining whether the parent is stressed or relieved, for example.

[2867] Step 19:

[2868] server

[2869] Based on the results of the emotion engine, the generative AI model generates a message that best matches the parent's emotions. For example, if the parent is tired, it generates a message such as, "Thank you for your hard work today. It's important to take a short rest."

[2870] Step 20:

[2871] server

[2872] Send the generated message to the terminal.

[2873] Step 21:

[2874] Terminal

[2875] The device notifies the parent of the message, who then views the message.

[2876] Step 22:

[2877] User

[2878] Parents can schedule a private consultation with a specialist using the options within the app, inputting the desired date and time and the content of the consultation.

[2879] Step 23:

[2880] Terminal

[2881] The terminal transmits the reservation information to the server.

[2882] Step 24:

[2883] server

[2884] The server notifies the specialist of the reservation information and obtains confirmation.

[2885] Step 25:

[2886] Expert

[2887] Experts will interact with parents online at designated times and provide personalized advice.

[2888] Step 26:

[2889] User

[2890] Parents can consult with an expert through the app at a designated time and receive necessary advice.

[2891] This means that AI Nentore not only manages babies' sleep, but also provides psychological support to parents, making it a comprehensive sleep support system.

[2892] Example 2

[2893] 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."

[2894] In today's world, it is extremely difficult for parents to properly manage their baby's sleep and maintain an optimal sleep schedule. New parents, in particular, often experience stress due to a lack of knowledge about their baby's sleep patterns, which prevents them from responding appropriately. Furthermore, parents often ignore their own emotional state, which increases parenting stress. Another problem is the lack of easy access to individual consultations with specialists.

[2895] 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.

[2896] In this invention, the server includes input means for parents to input their baby's sleep data, analysis means for receiving and analyzing the data input from the input means, and schedule generation means for generating an optimal sleep schedule for the baby based on the data analyzed by the analysis means, according to the baby's age and developmental stage. This allows parents to appropriately manage their baby's sleep status and maintain an optimal sleep schedule.

[2897] The "input means" is an interface that allows parents to input their baby's sleep data and basic information.

[2898] The "analysis means" is a system for analyzing the data received from the input means and identifying the baby's sleep patterns.

[2899] The "schedule generation means" is a system for generating an optimal sleep schedule according to the baby's age and developmental stage based on the data obtained by the analysis means.

[2900] The "notification means" is a system for notifying parents of the generated sleep schedule so that the parents can be aware of the schedule.

[2901] The "schedule adjustment tool" is a system for correcting and adjusting existing sleep schedules based on new sleep data entered by parents.

[2902] The "message generating means" is a system for providing psychological support messages to parents.

[2903] The "emotion engine means" is a system for analyzing input text, voice, and biometric information to identify the parent's emotional state.

[2904] The "emotion message generating means" is a system for generating an appropriate message based on the parent's emotional state identified by the emotion engine means.

[2905] The "consultation reservation means" is a system that allows parents to make reservations for individual consultations with specialists.

[2906] This invention is a comprehensive childcare support system that combines a system that analyzes and generates an optimal sleep schedule based on the input of a parent's baby's sleep data, with an emotion engine that recognizes the user's emotions. This system aims to not only optimize a baby's sleep environment, but also to reduce the psychological burden on parents.

[2907] Enter your baby's basic information and sleep data

[2908] User

[2909] Parents first enter their baby's basic information (name, age, gender, etc.) into the app, then enter their daily sleep data (wake-up time, bedtime, nap time, frequency of nighttime crying, etc.).

[2910] Terminal

[2911] The terminal transmits the input data to the server. For example, a device equipped with a user interface, such as a smartphone or tablet, is used.

[2912] server

[2913] The server stores the received data in a database (e.g., MySQL, PostgreSQL, etc.). The stored data undergoes initial analysis using analytical tools. For example, analytical software such as Python or R can be used.

[2914] Generation and presentation of optimal sleep schedule

[2915] server

[2916] The server uses a generative AI model (e.g., OpenAI GPT-3) based on the analyzed data to generate an optimal sleep schedule for the baby based on their age and developmental stage. This schedule includes bedtime and nap times. The generated schedule is then sent to the device.

[2917] Terminal

[2918] The device will notify parents of the generated sleep schedule via a pop-up message or alert.

[2919] Schedule adjustments

[2920] User

[2921] Parents re-enter new sleep data, including whether the sleep plan was met and the actual sleep duration.

[2922] Terminal

[2923] The terminal transmits the newly entered data to the server.

[2924] server

[2925] The server will automatically adjust the schedule based on the new data, and the next suggested schedule will be revised to something like "Go to bed at 8 PM, take 1.5 hour naps at 10 AM and 2 PM."

[2926] Providing psychological support

[2927] server

[2928] The server uses a generative AI model to automatically generate encouragement and advice that is sensitive to the parent's feelings. For example, the day after a night of heavy crying, it might generate a message like, "Today was tough, but this is part of growing up. You're a great mom."

[2929] Terminal

[2930] The device notifies the parent of this automatically generated message.

[2931] Individual consultation with an expert

[2932] User

[2933] Within the app, parents select the option to book a private consultation with a specialist and enter the desired date and time and the details of the consultation.

[2934] Terminal

[2935] The terminal transmits the reservation information to the server.

[2936] server

[2937] The server notifies the specialist of the reservation information and obtains confirmation.

[2938] Expert

[2939] Experts will interact with parents online at designated times and provide personalized advice.

[2940] Recognizing user emotions with an emotion engine

[2941] Terminal

[2942] The text, voice data, and even biometric information (e.g., heart rate, facial expressions, etc.) that parents enter into the app are sent to the emotion engine.

[2943] server

[2944] The server's emotion engine analyzes this data and identifies the parent's emotional state, for example, by analyzing emotions such as "stress" or "fatigue" from the text data.

[2945] Emotion-based message generation

[2946] server

[2947] Based on the analysis results of the emotion engine, the generative AI model generates a message appropriate to that emotion. For example, if a parent is tired, it might generate a message such as, "Thank you for your hard work today. It's important to take a short rest."

[2948] Terminal

[2949] The generated message is sent to the device and notified to the parent, allowing the parent to receive support appropriate to the child's emotions at that time.

[2950] Specific examples

[2951] Example 1: Initial Setup and Data Entry

[2952] User: Downloads and launches the app, then enters the baby's name as "Taro," its age as "6 months," and its gender as "male."

[2953] Terminal: Sends the entered information to the server.

[2954] Server: Receives the information, stores it in a database, and begins initial analysis.

[2955] Example 2: Schedule Generation

[2956] User: Enter sleep data (e.g., went to bed at 7pm, cried twice at night, woke up at 6am, took one hour nap at 10am and one hour nap at 2pm).

[2957] Terminal: Sends the entered data to the server.

[2958] Server: Analyzes the data using a generative AI model and generates the next schedule, suggesting "Go to bed at 8pm, take 1 hour and 30 minute naps at 10am and 2pm."

[2959] Example 3: Psychological support through an emotional engine

[2960] User: Texts "I'm so tire...

Claims

1. an input means for a parent to input the baby's sleep data; analysis means for receiving and analyzing data input from the input means; a schedule generating means for generating an optimal sleep schedule according to the baby's age and growth stage based on the data analyzed by the analyzing means; a notification means for notifying a parent of the sleep schedule generated by the schedule generation means; a schedule adjustment tool to modify and adjust the schedule based on new sleep data entered by the parent; a message generating means for providing psychological support messages to parents; A consultation reservation method for individual consultations with experts; A system including:

2. 2. The system according to claim 1, wherein the input means comprises a user interface that allows a parent to input information such as the baby's sleeping time, waking time, nap time, and frequency of night crying.

3. 10. The system of claim 1, wherein the analyzing means includes means for analyzing sleep patterns using a generative artificial intelligence model.

4. 2. The system according to claim 1, wherein said schedule generating means includes means for proposing optimal sleep timing taking into consideration the baby's age in months and living environment.

5. 2. The system according to claim 1, wherein the message generating means includes means for automatically generating encouragement or advice that is sensitive to the feelings of parents.

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