system

Abstract

We provide the system. [Solution] A method for calculating the optimal bedtime based on a child's age and daily routine, To automatically adjust the child's sleep environment, a means of linking with home devices, A method for automatically selecting and providing music and stories that are effective for getting children to sleep, A means of analyzing children's sleep data and providing parents with advice on appropriate physical touch and verbal communication, A way to prompt a reminder as bedtime approaches, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern society, it is difficult to establish sleep habits in families with preschool children, and the burden on parents is particularly heavy. There are also problems such as a shortage of sleep experts and difficulty in finding a bedtime method suitable for each child. This raises concerns about hindering the healthy growth of children. Therefore, there is a need to provide a method that can reduce the burden on parents and enable children to acquire appropriate sleep habits.

Means for Solving the Problems

[0005] This invention provides a system that includes means for calculating the optimal bedtime based on a child's age and lifestyle, means for automatically adjusting the sleep environment in conjunction with home devices, means for automatically selecting and providing music and stories effective for lullabies, means for analyzing sleep data and providing parents with advice on appropriate physical touch and verbal communication, and means for sending reminders as bedtime approaches. This system enables individualized support tailored to each family's situation and helps children develop healthy sleep habits. Furthermore, the system's effectiveness is continuously enhanced by utilizing feedback to improve the accuracy of its suggestions.

[0006] "A child's age and daily routine" refers to a child's age and cyclical habits, including their daily wake-up and bedtime.

[0007] "Methods for calculating bedtime" refers to methods and techniques for calculating the most appropriate bedtime for a child based on their age and daily routine.

[0008] "Household devices" refer to electronic devices used within the home, such as smartphones, computers, smart speakers, and smart lights.

[0009] "Methods for automatically adjusting the sleep environment" refer to technologies that use home devices to automatically optimize lighting and temperature settings to create a suitable sleep environment for children.

[0010] "Effective music and stories for putting children to sleep" refers to music and stories designed to soothe and relax children, helping them fall asleep.

[0011] "Means of analyzing sleep data" refers to methods and techniques for collecting and analyzing data on children's sleep patterns and responses.

[0012] "Advice on physical touch and verbal communication" refers to information that instructs parents on specific ways of touching and speaking to their children in order to calm them down and help them fall asleep comfortably.

[0013] "Methods for sending reminders" refer to methods and technologies for notifying parents or children when bedtime is approaching.

[0014] "Feedback" refers to information obtained after using the system regarding the child's reactions and sleep patterns, and this information is used as data to improve the system.

[0015] "Artificial intelligence" refers to the technology that allows computers to mimic human intelligence, enabling them to make optimal decisions through data analysis and pattern recognition. [Brief explanation of the drawing]

[0016] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] Shows an emotion map to which a plurality of emotions are mapped. [Figure 10] Shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Mode for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be described.

[0019] In the following embodiments, a processor with a reference numeral (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of a plurality of types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0020] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0021] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

[0025] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0026] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0036] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0037] This invention presents an embodiment of a system that suggests an optimal bedtime based on a child's age and current sleep schedule, and supports bedtime routines. The system begins with the user inputting basic information about the child via a terminal, and the server uses this information to select an individually optimized bedtime along with content effective for bedtime. This reduces the burden on parents while simultaneously helping children develop regular sleep habits.

[0038] The device first provides an interface for the user to input basic information about the child, such as age, daily routine, and bedtime preferences. Next, the device sends this data to the server and instructs it to process it.

[0039] The server analyzes the received data. Based on age and previous data, an AI algorithm calculates the most suitable bedtime for the child. Furthermore, it automatically selects the most suitable music or stories to promote relaxation before bedtime and instructs the device to play them. Through these processes, the server creates an environment that naturally lulls the child to sleep. The server also works in conjunction with the home's smart devices to automatically adjust the room lighting and temperature to a state suitable for sleep.

[0040] Furthermore, the server collects and analyzes sleep data, taking past history into consideration, and notifies parents with specific advice on body language and verbal cues tailored to each child. This allows parents to get their children to sleep using a more effective approach.

[0041] For example, in a family with a three-year-old child, if the child is having more trouble falling asleep than usual, the server will adjust the usual bedtime based on the child's past sleep data and current situation, and select calming music. It will then provide specific advice to the parents, such as "gently stroke their back and speak to them in a calm voice," supporting a more natural approach to putting the child to sleep.

[0042] This system allows for flexible adaptation to seasonal changes and shifts in daily routines, making it possible to continuously manage and improve children's sleep.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] The user accesses a dedicated app on their device and enters basic information such as the child's age, usual wake-up time, and preferred types of bedtime music or stories. The device then sends this data to the server.

[0046] Step 2:

[0047] The server inputs the child's basic information into an AI algorithm and calculates the optimal bedtime based on the child's age and daily routine. The server then sends this result to the device.

[0048] Step 3:

[0049] The device notifies the user of the optimal bedtime received from the server. The user can review the information and make adjustments as needed.

[0050] Step 4:

[0051] As bedtime approaches, the server uses AI to select music and stories tailored to the child's age and preferences. The server then sends this selection to the device and instructs it to begin playback.

[0052] Step 5:

[0053] The device plays selected music or stories based on instructions from the server, helping the child relax.

[0054] Step 6:

[0055] The server connects with smart devices in the home (such as smart lights and air conditioners) and automatically adjusts lighting and temperature settings to create a suitable sleep environment for children.

[0056] Step 7:

[0057] The server monitors and analyzes children's sleep data in real time and sends specific advice to the user's device regarding optimal physical contact and verbal communication.

[0058] Step 8:

[0059] The server sends a reminder to the user via the device a little before bedtime, encouraging the child to prepare for bed smoothly.

[0060] Step 9:

[0061] The user enters feedback on the child's sleep quality and bedtime process into the device. The device then sends this information to the server.

[0062] Step 10:

[0063] The server incorporates user feedback to continuously improve its AI model and enhance the accuracy of future suggestions and support.

[0064] (Example 1)

[0065] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0066] In today's busy lifestyle, many parents find it difficult to properly manage their children's sleep habits, resulting in situations where children don't get enough sleep. In particular, setting appropriate bedtimes and adjusting the sleep environment to suit each individual child is challenging, highlighting the need for support to ensure children get consistent sleep. Furthermore, parents have limited opportunities to learn effective methods for getting their children to sleep.

[0067] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0068] In this invention, the server includes means for calculating the optimal bedtime based on the child's age and daily activities, means for coordinating with a home control device to automatically adjust the child's sleeping environment, and means for automatically selecting and providing audio and video content effective for the child's pre-sleep activities. This makes it possible for each household to receive sleep support optimized for each individual child.

[0069] "Child's age" refers to the number of years calculated from the child's date of birth, which is fundamental information for optimizing sleep.

[0070] "Daily activities" refer to the typical behaviors and routines that children engage in on a daily basis, and these influence the calculation of bedtime.

[0071] "Optimal bedtime" refers to the time a child should fall asleep, calculated based on scientific evidence to support a child's healthy sleep patterns.

[0072] A "household control device" is an electronic device used to manage and adjust environmental elements such as lighting and temperature within the home.

[0073] "Sleep environment" refers to all the physical and sensory environmental elements that need to be prepared for a child to sleep comfortably.

[0074] "Audio and video" refers to sound and visual content used to promote relaxation and sleep in children.

[0075] "Parent" is a general term for guardians who are involved in raising children and who need to manage their bedtime habits.

[0076] A "user interface" refers to the screens and input devices that parents use to input information about their children and to operate services.

[0077] This invention is a system that supports the formation of optimal sleep habits based on a child's age and daily activities. The system mainly consists of a terminal, a server, and a home control unit.

[0078] The devices used by users are mobile devices such as smartphones and tablets, and a user interface is provided for parents to input basic information about their children. Parents input their child's age, daily activity information, and bedtime preferences through the device.

[0079] The information collected by the device is sent to a server via the internet. The server receives this data and uses an AI algorithm to calculate the optimal bedtime. This AI model has the ability to analyze large amounts of sleep data and extract appropriate patterns.

[0080] The server also works in conjunction with the home control system to automatically adjust the room lighting and temperature, creating an environment suitable for sleep. The selected audio and video content promotes relaxation in children and supports smooth sleep.

[0081] As a concrete example, when a user enters information about a 3-year-old child, the server uses that data to compare it with past cases and suggests an appropriate bedtime. Furthermore, it adjusts the room environment through a home control device and starts playing relaxing stories or music from the device.

[0082] An example of a prompt message is: "If a 3-year-old child has trouble falling asleep, please provide specific instructions on how to select an appropriate bedtime and music based on past sleep data, and what kind of sleep-training advice to offer the parents. Furthermore, please explain how to use smart devices to create an ideal bedroom environment."

[0083] This system allows parents to efficiently manage their children's sleep and receive support in establishing a better daily routine.

[0084] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0085] Step 1:

[0086] The user enters basic information about their child into the device. Specifically, the user enters information such as the child's age, daily routine, and bedtime preferences through the interface. This information is used as basic data for the system to calculate the optimal bedtime. The entered data is encrypted and sent to the server.

[0087] Step 2:

[0088] The terminal sends input information to the server. The terminal sends data received from the user to the server in real time. The transmitted information is stored in the server's database and prepared for analysis by AI algorithms.

[0089] Step 3:

[0090] The server analyzes the data to calculate the optimal bedtime. The AI ​​model within the server references the received data (age, activity patterns, etc.) to determine the optimal bedtime. This analysis utilizes historical statistical data and scientific research findings. As a result, a personalized bedtime is calculated for each individual child.

[0091] Step 4:

[0092] The server selects the most suitable content and issues instructions to the device. Based on the calculated bedtime, the server uses an AI algorithm to select audio and video content to help the child relax. The selected content is notified to the device, informing the user that it is ready for playback.

[0093] Step 5:

[0094] The server issues instructions to the home control unit to adjust the environment. The server communicates with smart home devices and issues commands to change the room lighting to a warmer color and adjust the temperature according to the designated bedtime. This automatically creates an optimal environment for sleeping.

[0095] Step 6:

[0096] The server provides users with specific advice on getting their children to sleep. The server sends notifications to the user's device, displaying specific advice to help with getting the child to sleep. This advice is generated based on past data analysis and the current situation. This allows parents to support effective bedtime routines.

[0097] Step 7:

[0098] The server collects sleep data and uses it for subsequent analysis. The server collects data on the child's sleep patterns from devices and home sensors. This data is used to optimize bedtimes and generate advice for future sessions, thereby enabling continuous improvement.

[0099] (Application Example 1)

[0100] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0101] Setting and achieving ideal rest schedules for children is a major challenge for parents. In particular, there is a lack of customized suggestions based on individual child information, highlighting the need for effective ways to support children in falling asleep naturally. Furthermore, existing methods are insufficient in providing appropriate feedback on children's reactions and conditions to deliver highly accurate sleep suggestions.

[0102] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0103] In this invention, the server includes means for calculating an ideal rest period based on the child's individual information and daily rhythm; means for automatically adjusting the child's sleep environment in interaction with childcare equipment; and means for providing a function for a robot to naturally guide the child to sleep while interacting with them. This enables personalized support to help children get regular rest and reduces the burden on parents.

[0104] "Individualized information" refers to specific data about an individual child, including their age, daily activities, and bedtime preferences.

[0105] "Daily routine" refers to the patterns and schedules of daily life that a child usually follows.

[0106] "Ideal rest time" refers to the recommended bedtime to ensure the most beneficial amount of sleep for a child's health and growth.

[0107] "Child development equipment" refers to electronic devices and systems used within the home to support a child's development and daily life.

[0108] A "sleep environment" refers to the totality of physical conditions such as lighting, temperature, and sound in a room that are arranged to allow a child to sleep comfortably.

[0109] "Audio content" refers to sound information such as music and stories used to promote relaxation and sleepiness in children.

[0110] "Response and rest state feedback" refers to the collection of information about a child's behavior and sleep quality, and the system's suggestions for improvement based on that information.

[0111] Artificial intelligence is a computer technology that uses programmed algorithms to understand problems and generate solutions in a way that is similar to humans.

[0112] The "function to naturally induce sleep through dialogue" refers to the ability of a robot to communicate with a child while creating an environment conducive to falling asleep.

[0113] This system aims to help children set their ideal rest schedule and support the process. The server receives individual information about the child from the user, such as age, daily routine, and bedtime preferences, and uses this information to calculate the optimal rest time. Furthermore, the server works in conjunction with childcare equipment to automatically optimize the child's sleep environment. Specifically, it controls smart home devices to optimize lighting and temperature.

[0114] The server also uses a generative AI model to analyze and select audio content suitable for children. This content includes music and stories designed to help children relax. For example, by sending a prompt such as, "Please recommend stories to help a 3-year-old child calm down and fall asleep," the AI ​​will select appropriate audio content.

[0115] Furthermore, the server collects feedback on the child's reactions and sleep patterns, and uses artificial intelligence to improve the accuracy of rest suggestions. This allows parents to receive personalized advice and more effectively support their child's sleep. For example, it can flexibly respond by adding another story if the child finishes listening to their favorite story or music too quickly. The robot also has a function to naturally guide the child to sleep when interacting with them. This allows children to fall asleep peacefully even when their parents are not present.

[0116] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0117] Step 1:

[0118] The user enters individual information about their child via a device. This information includes age, daily routine, and bedtime preferences. This data is then sent to the server.

[0119] Step 2:

[0120] Based on the individual information it receives, the server uses a generative AI model to calculate the ideal rest time. To analyze the input data, the server considers age and daily rhythm to calculate the optimal bedtime. The calculation result is output as a recommended bedtime.

[0121] Step 3:

[0122] The server selects audio content. Using a generative AI model, it takes the prompt "Please recommend audio content to help children fall asleep" as input and selects suitable music or stories. This process outputs audio content that has a relaxing effect on children.

[0123] Step 4:

[0124] The server works in conjunction with childcare equipment to automatically optimize the child's sleep environment. The server sends instructions to smart home devices that control lighting and temperature, and based on the optimal environmental conditions obtained as input, it produces outputs such as dimming the lights or adjusting the temperature.

[0125] Step 5:

[0126] The server collects feedback on the child's responses and resting state during sleep. This feedback is collected as input from sensor devices and analyzed by the server. The analysis results are used to output data to improve the accuracy of rest suggestions.

[0127] Step 6:

[0128] The server provides personalized advice to parents. Based on the analysis results, the server generates specific advice on "timing of physical contact" and "methods of conversation" and notifies parents via message. This advice notification is the output.

[0129] Step 7:

[0130] The robot utilizes its conversational capabilities to naturally guide children to sleep. It plays audio content selected by the server, creating a relaxing environment through communication with the child. At this stage, the output is to guide the child to fall asleep peacefully.

[0131] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0132] This invention describes a form of a child sleep support system that incorporates an emotion engine that analyzes the user's emotions in real time. In addition to conventional sleep habit support, this system also takes into account the emotional state of the parents, thereby providing a more effective and personalized sleep environment.

[0133] The user enters the child's basic information into the device and sets their daily sleep patterns. The device sends this data to the server. Based on the received information, the server uses AI to calculate the optimal bedtime and analyzes the user's emotional data using an emotion engine.

[0134] The emotion engine analyzes the user's emotional state in real time based on their voice tone, facial expressions, and other factors. Based on this analysis, the server selects music and stories that are more suitable for the child and sends instructions to the home smart device to adjust the sleep environment as needed.

[0135] For example, if the server detects that the user is feeling fatigued or stressed, it will select relaxing music or short stories. It will then provide advice to the parent through the device, such as "tell a short story in a slow, gentle voice." It may also dim the room lights to create a calming environment.

[0136] Furthermore, after the bedtime process is successful, the user provides feedback via their device. This information is also analyzed on the server and used to improve the AI ​​algorithm. This allows the system to be continuously optimized and provide support tailored to individual home environments.

[0137] In this way, the present invention efficiently supports sleep habits that are suitable for individual children and parents by taking into account the emotional state of the user.

[0138] The following describes the processing flow.

[0139] Step 1:

[0140] The user launches the application on their device and enters information such as the child's age, normal sleep schedule, and preferred bedtime content. This prepares the system for setting up an individual sleep plan.

[0141] Step 2:

[0142] The device sends the data entered by the user to the server. The server receives this data and, at the user's request, uses an AI algorithm to calculate the optimal bedtime for the child.

[0143] Step 3:

[0144] The device is equipped with a mechanism to capture the user's voice and video, which is used to record the user's emotional state in real time. The emotion engine analyzes the user's voice tone and facial expressions.

[0145] Step 4:

[0146] The server receives the user's emotional data, analyzed by the emotion engine, and selects the most suitable music and stories for the child. These options are then sent to the device and presented to the child.

[0147] Step 5:

[0148] As bedtime approaches, the server sends instructions to smart devices in the home, such as adjusting the lighting and managing the temperature, to automatically create the most suitable sleep environment for the child.

[0149] Step 6:

[0150] The device plays content sent from the server and simultaneously notifies the user of advice based on the analysis results. For example, it might suggest actions such as "Take a deep breath and speak gently to your child."

[0151] Step 7:

[0152] After bedtime, users provide feedback via their device regarding their child's sleep onset and quality. The device sends this feedback to a server, which then uses the feedback to improve the AI ​​model.

[0153] Step 8:

[0154] Based on feedback and sentiment data, the server further personalizes future suggestions, continuously improving the overall effectiveness of the system.

[0155] (Example 2)

[0156] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0157] Sleep deprivation among children and parental stress are serious problems in modern society. In particular, there is a lack of sleep support methods tailored to each child's individual needs, and support that considers the impact of parental emotional state on a child's sleep is insufficient. Furthermore, there is a need to dynamically adjust the sleep environment so that parents can easily provide optimal care according to their child's condition.

[0158] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0159] In this invention, the server includes means for analyzing the parent's emotional state and providing sleep support information based on that state, means for calculating the optimal bedtime based on the child's age and lifestyle patterns, and means for coordinating with home appliances to automatically adjust the child's sleep environment. This enables personalized sleep support that takes the parent's emotional state into account, and dynamic adjustment of the sleep environment according to the child's daily rhythm.

[0160] "Analyzing a parent's emotional state" refers to using data such as the tone of their voice and facial expressions to evaluate their emotional state in real time.

[0161] "Providing sleep support information" refers to the act of offering parents specific advice, selected music, or stories to promote their children's sleep.

[0162] "Calculating the optimal bedtime" means determining the most appropriate bedtime for a given day based on the child's age and lifestyle.

[0163] "Automatically adjusting the sleep environment" refers to the process of adjusting elements such as volume, lighting, and temperature in conjunction with household devices to create an optimal sleep environment.

[0164] "Household appliances" refer to devices installed in the home, including smart devices, such as music players, lighting, and speakers.

[0165] "Artificial intelligence" refers to a technology that analyzes large amounts of data and performs advanced reasoning and learning based on the results, contributing to improving the accuracy of sleep recommendations.

[0166] "Providing an interface" refers to providing a user interface or device that allows parents to input information about their children and to recognize the parents' emotional state.

[0167] This invention is a system that supports children's sleep and provides personalized services that take into account the emotional state of the parents. First, the user inputs basic information about the child, such as age and lifestyle patterns, using a terminal. The terminal sends this data to a server. Based on the received information, the server operates a generating AI model to calculate the optimal bedtime. The AI ​​model refers to past sleep data and generates advice tailored to the individual's lifestyle rhythm.

[0168] The server also uses an emotion engine to analyze the user's voice tone and facial expressions in real time. This allows for the provision of detailed support information based on the parent's emotional state. For example, if the parent is feeling stressed or fatigued, relaxing music or stories will be selected to help the child fall asleep more easily.

[0169] Smart speakers and smart lighting are used to integrate with home appliances. The server sends instructions to these devices to play music or adjust lighting. This automatically optimizes the child's sleep environment. Furthermore, parents can provide feedback from their devices, and this information is used by the server to improve the AI ​​model, thereby increasing the accuracy of future suggestions.

[0170] For example, if a user enters "Please suggest a list of music that will help my child relax" into their device, the server uses an AI model to generate a list and plays it through a smart speaker. In this way, the system supports children and parents in enjoying a better bedtime environment.

[0171] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0172] Step 1:

[0173] Users input basic information about their child and their daily sleep patterns through their device. This information includes the child's age, typical bedtime and wake-up times, and daytime activities. This information is stored in a database and prepared for transmission to the server.

[0174] Step 2:

[0175] The terminal encrypts the information entered by the user and sends it to the server. The server stores the received data in a database and verifies the integrity of the information. A data check is performed here to check for missing values ​​or inconsistencies.

[0176] Step 3:

[0177] The server runs an AI model based on the child's information to calculate the optimal bedtime. The AI ​​model also references past sleep data, combining it with the input data to generate an optimized bedtime schedule. The calculated bedtime is then sent back to the device as feedback from the server.

[0178] Step 4:

[0179] The server uses an emotion engine to analyze the user's voice tone and facial expressions. When the user inputs audio or video into the device, their emotional state is evaluated in real time. Based on this analysis, sleep support information tailored to the parent's emotional state is generated.

[0180] Step 5:

[0181] Based on the analysis results, the server works in conjunction with home devices to select suitable music and stories. The selected content is played through a smart speaker, and simultaneously, the brightness of smart lighting and other settings are adjusted. This optimizes the sleep environment in real time.

[0182] Step 6:

[0183] Users provide feedback via their device about their child's behavior after bedtime and their own observations. This feedback is collected on a server and used to improve the AI ​​model. Based on the collected data, the system is programmed to automatically improve the accuracy of its suggestions.

[0184] (Application Example 2)

[0185] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0186] There is a need for effective means to provide an appropriate sleep environment that takes into account the emotional state and sleep quality of the elderly, thereby promoting individual health maintenance. Conventional technologies provide sleep support based on general patterns and do not adequately consider individual emotions or health conditions. As a result, optimal sleep support is not provided, and there is room for improvement to suit individual circumstances.

[0187] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0188] In this invention, the server includes means for calculating the optimal bedtime based on an individual's age and lifestyle, means for analyzing an individual's emotional state and providing appropriate music or stories, and means for giving instructions to optimize the environment based on the emotional analysis. This makes it possible to take into account the emotional state of elderly people and provide a sleep environment that is tailored to their individual needs.

[0189] "Age and lifestyle" refers to an individual's age and daily routine, and serves as a standard for providing care tailored to their individual health and lifestyle rhythms.

[0190] "Optimal bedtime" refers to the ideal time to start sleep to obtain adequate rest, based on an individual's health condition and daily activities.

[0191] "Emotional state" refers to an individual's emotional reactions and psychological state, which are assessed through tone of voice and facial expressions.

[0192] "Household appliances" refer to digital devices used within the home, including devices that control the environment such as lighting and sound equipment.

[0193] "Music and stories" refers to audio content selected according to an individual's mood or state, with the aim of promoting relaxation and sleep.

[0194] "Artificial intelligence" refers to a computer system that makes autonomous decisions through data analysis, prediction, optimization, and other processes.

[0195] An "interface" refers to a point of contact or method for a user to interact with a system, enabling the input and output of information.

[0196] The system that realizes this application provides an optimal sleep environment based on an individual's emotional state, age, and lifestyle. Specifically, it uses the following hardware and software.

[0197] The server calculates the appropriate bedtime based on an individual's age, lifestyle, and past response data. It receives data transmitted by the user via devices such as smart glasses or smartphones, and this data is analyzed using an AI algorithm. Using Google® Cloud Vision API as an example, it analyzes facial expressions captured by a camera and analyzes audio data using Amazon Polly. Based on these analysis results, it selects the most suitable music or story to create a relaxation environment tailored to the individual's mental and physical state.

[0198] Users receive environmental instructions and advice via their devices and adjust their actual environment using smart glasses and audio equipment. Lighting and music are automatically optimized, allowing individuals to naturally relax and fall asleep.

[0199] For example, if an elderly person feels anxious, the system will execute instructions such as "play relaxing music and dim the lamps" based on the analyzed data. A specific example of a prompt would be, "Please tell me how to infer emotions from an elderly person's voice and facial expression data and suggest relaxing music and environmental adjustments." This system enables flexible sleep support tailored to individual needs.

[0200] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0201] Step 1:

[0202] The user captures their personal facial expressions and voice using the camera and microphone through smart glasses and sends the data to the device. The input data consists of facial image data and audio data. The device then prepares to send this data to the server.

[0203] Step 2:

[0204] The server analyzes the received facial expression data using the Google Cloud Vision API to determine the individual's emotional state. The input is image data of facial expressions, and the output is a judgment of the emotional state (e.g., relaxed, anxious, stressed). This analysis determines the requirements for the next content to be provided.

[0205] Step 3:

[0206] The audio data is analyzed using Amazon Polly or similar voice analysis technologies to determine the tone of the voice. The input is audio data, and the output is the analysis results regarding emotional nuances and states. The server uses these results to determine the individual's current psychological state.

[0207] Step 4:

[0208] The server selects music or stories best suited to the individual based on the analysis results. This selection process utilizes music service APIs such as Pandora. The input is the result of the emotional state assessment, and the output is data of the selected music or story.

[0209] Step 5:

[0210] The system sends specific instructions regarding lighting and music to the user's device. Based on these instructions, the device controls household appliances (such as smart lights and speakers) to optimize the environment. The input is the instructions from the server, and the output is the adjusted indoor environment.

[0211] Step 6:

[0212] After going to sleep, users send feedback about their sleep status and satisfaction level from their device to the server. The input is subjective feedback data from the user, and the output is data used to train and improve the AI ​​model. The server analyzes this feedback and uses it to improve the accuracy of future service delivery.

[0213] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0214] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0215] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0216] [Second Embodiment]

[0217] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0218] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0219] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0220] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0221] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0222] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0223] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0224] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0225] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0226] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0227] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0228] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0229] This invention presents an embodiment of a system that suggests an optimal bedtime based on a child's age and current sleep schedule, and supports bedtime routines. The system begins with the user inputting basic information about the child via a terminal, and the server uses this information to select an individually optimized bedtime along with content effective for bedtime. This reduces the burden on parents while simultaneously helping children develop regular sleep habits.

[0230] The device first provides an interface for the user to input basic information about the child, such as age, daily routine, and bedtime preferences. Next, the device sends this data to the server and instructs it to process it.

[0231] The server analyzes the received data. Based on age and previous data, an AI algorithm calculates the most suitable bedtime for the child. Furthermore, it automatically selects the most suitable music or stories to promote relaxation before bedtime and instructs the device to play them. Through these processes, the server creates an environment that naturally lulls the child to sleep. The server also works in conjunction with the home's smart devices to automatically adjust the room lighting and temperature to a state suitable for sleep.

[0232] Furthermore, the server collects and analyzes sleep data, taking past history into consideration, and notifies parents with specific advice on body language and verbal cues tailored to each child. This allows parents to get their children to sleep using a more effective approach.

[0233] For example, in a family with a three-year-old child, if the child is having more trouble falling asleep than usual, the server will adjust the usual bedtime based on the child's past sleep data and current situation, and select calming music. It will then provide specific advice to the parents, such as "gently stroke their back and speak to them in a calm voice," supporting a more natural approach to putting the child to sleep.

[0234] This system allows for flexible adaptation to seasonal changes and shifts in daily routines, making it possible to continuously manage and improve children's sleep.

[0235] The following describes the processing flow.

[0236] Step 1:

[0237] The user accesses a dedicated app on their device and enters basic information such as the child's age, usual wake-up time, and preferred types of bedtime music or stories. The device then sends this data to the server.

[0238] Step 2:

[0239] The server inputs the child's basic information into an AI algorithm and calculates the optimal bedtime based on the child's age and daily routine. The server then sends this result to the device.

[0240] Step 3:

[0241] The device notifies the user of the optimal bedtime received from the server. The user can review the information and make adjustments as needed.

[0242] Step 4:

[0243] As bedtime approaches, the server uses AI to select music and stories tailored to the child's age and preferences. The server then sends this selection to the device and instructs it to begin playback.

[0244] Step 5:

[0245] The device plays selected music or stories based on instructions from the server, helping the child relax.

[0246] Step 6:

[0247] The server connects with smart devices in the home (such as smart lights and air conditioners) and automatically adjusts lighting and temperature settings to create a suitable sleep environment for children.

[0248] Step 7:

[0249] The server monitors and analyzes children's sleep data in real time and sends specific advice to the user's device regarding optimal physical contact and verbal communication.

[0250] Step 8:

[0251] The server sends a reminder to the user via the device a little before bedtime, encouraging the child to prepare for bed smoothly.

[0252] Step 9:

[0253] The user enters feedback on the child's sleep quality and bedtime process into the device. The device then sends this information to the server.

[0254] Step 10:

[0255] The server incorporates user feedback to continuously improve its AI model and enhance the accuracy of future suggestions and support.

[0256] (Example 1)

[0257] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0258] In today's busy lifestyle, many parents find it difficult to properly manage their children's sleep habits, resulting in situations where children don't get enough sleep. In particular, setting appropriate bedtimes and adjusting the sleep environment to suit each individual child is challenging, highlighting the need for support to ensure children get consistent sleep. Furthermore, parents have limited opportunities to learn effective methods for getting their children to sleep.

[0259] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0260] In this invention, the server includes means for calculating the optimal bedtime based on the child's age and daily activities, means for coordinating with a home control device to automatically adjust the child's sleeping environment, and means for automatically selecting and providing audio and video content effective for the child's pre-sleep activities. This makes it possible for each household to receive sleep support optimized for each individual child.

[0261] "Child's age" refers to the number of years calculated from the child's date of birth, which is fundamental information for optimizing sleep.

[0262] "Daily activities" refer to the typical behaviors and routines that children engage in on a daily basis, and these influence the calculation of bedtime.

[0263] "Optimal bedtime" refers to the time a child should fall asleep, calculated based on scientific evidence to support a child's healthy sleep patterns.

[0264] A "household control device" is an electronic device used to manage and adjust environmental elements such as lighting and temperature within the home.

[0265] "Sleep environment" refers to all the physical and sensory environmental elements that need to be prepared for a child to sleep comfortably.

[0266] "Audio and video" refers to sound and visual content used to promote relaxation and sleep in children.

[0267] "Parent" is a general term for guardians who are involved in raising children and who need to manage their bedtime habits.

[0268] A "user interface" refers to the screens and input devices that parents use to input information about their children and to operate services.

[0269] This invention is a system that supports the formation of optimal sleep habits based on a child's age and daily activities. The system mainly consists of a terminal, a server, and a home control unit.

[0270] The devices used by users are mobile devices such as smartphones and tablets, and a user interface is provided for parents to input basic information about their children. Parents input their child's age, daily activity information, and bedtime preferences through the device.

[0271] The information collected by the device is sent to a server via the internet. The server receives this data and uses an AI algorithm to calculate the optimal bedtime. This AI model has the ability to analyze large amounts of sleep data and extract appropriate patterns.

[0272] The server also works in conjunction with the home control system to automatically adjust the room lighting and temperature, creating an environment suitable for sleep. The selected audio and video content promotes relaxation in children and supports smooth sleep.

[0273] As a concrete example, when a user enters information about a 3-year-old child, the server uses that data to compare it with past cases and suggests an appropriate bedtime. Furthermore, it adjusts the room environment through a home control device and starts playing relaxing stories or music from the device.

[0274] An example of a prompt message is: "If a 3-year-old child has trouble falling asleep, please provide specific instructions on how to select an appropriate bedtime and music based on past sleep data, and what kind of sleep-training advice to offer the parents. Furthermore, please explain how to use smart devices to create an ideal bedroom environment."

[0275] This system allows parents to efficiently manage their children's sleep and receive support in establishing a better daily routine.

[0276] The flow of the specific process in Example 1 will be described with reference to FIG. 11.

[0277] Step 1:

[0278] The user inputs the basic information of the child into the terminal. Specifically, the user inputs information such as the child's age, daily life pattern, and preferences before going to bed into the terminal through the interface. This information is treated as the basic data for the system to calculate the optimal bedtime. The input data is encrypted and sent to the server.

[0279] Step 2:

[0280] The terminal sends the input information to the server. The terminal sends the data received from the user to the server in real time. The transmitted information is stored in the server's database, and preparations for analysis by the AI algorithm are made.

[0281] Step 3:

[0282] The server analyzes the data to calculate the optimal bedtime. The generative AI model in the server refers to the received data (age, activity pattern, etc.) and derives the optimal bedtime. Past statistical data and scientific research results are used in this analysis. As a result, a personalized bedtime for each child is calculated.

[0283] Step 4:

[0284] The server selects the optimal content and issues an instruction to the terminal. Based on the calculated bedtime, the server selects voice and video content for relaxing the child using the AI algorithm. The selected content is notified to the terminal, informing the user that the preparation for playback is complete.

[0285] Step 5:

[0286] The server gives instructions to the home control device to perform environmental adjustment. The server communicates with smart home devices and issues instructions to change the room lighting to a warm color tone and adjust the temperature according to a predetermined bedtime. As a result, an environment optimal for sleeping is automatically prepared.

[0287] Step 6:

[0288] The server provides specific bedtime advice to the user. The server sends a notification to the user's terminal and displays specific advice useful for putting a child to bed. This advice is generated based on the analysis of past data and the current situation. As a result, parents can support effective sleep.

[0289] Step 7:

[0290] The server collects sleep data for use in the next analysis. The server collects data on the child's sleep situation from terminals and home sensors. This data is used for the optimization of bedtime and the generation of advice in subsequent times. As a result, continuous improvement is achieved.

[0291] (Application Example 1)

[0292] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0293] Supporting the setting and realization of a child's ideal rest time is a major issue for guardians. In particular, due to the lack of customized proposals based on the child's individual information, there is a need for a method to effectively support the child to fall asleep naturally. Also, the process of appropriately providing feedback on the child's reactions and conditions and providing highly accurate sleep proposals has not been fully addressed by existing means.

[0294] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0295] In this invention, the server includes means for calculating an ideal rest period based on the child's individual information and daily rhythm; means for automatically adjusting the child's sleep environment in interaction with childcare equipment; and means for providing a function for a robot to naturally guide the child to sleep while interacting with them. This enables personalized support to help children get regular rest and reduces the burden on parents.

[0296] "Individualized information" refers to specific data about an individual child, including their age, daily activities, and bedtime preferences.

[0297] "Daily routine" refers to the patterns and schedules of daily life that a child usually follows.

[0298] "Ideal rest time" refers to the recommended bedtime to ensure the most beneficial amount of sleep for a child's health and growth.

[0299] "Child development equipment" refers to electronic devices and systems used within the home to support a child's development and daily life.

[0300] A "sleep environment" refers to the totality of physical conditions such as lighting, temperature, and sound in a room that are arranged to allow a child to sleep comfortably.

[0301] "Audio content" refers to sound information such as music and stories used to promote relaxation and sleepiness in children.

[0302] "Response and rest state feedback" refers to the collection of information about a child's behavior and sleep quality, and the system's suggestions for improvement based on that information.

[0303] Artificial intelligence is a computer technology that uses programmed algorithms to understand problems and generate solutions in a way that is similar to humans.

[0304] The "function of naturally leading to sleep while interacting" refers to the ability of the robot to create a situation conducive to falling asleep while communicating with children.

[0305] This system aims to set an ideal rest time for children and support the process. The server receives the individual information of the child input by the user, that is, age, daily rhythm, preferences before going to bed, etc., and calculates the optimal rest time based on this information. Furthermore, the server collaborates with the training equipment to automatically adjust the child's sleep environment. Specifically, it controls smart home devices to optimize lighting and temperature.

[0306] The server also performs analysis using a generative AI model and selects voice content suitable for the child. This content includes music, stories, etc., and is for promoting the relaxation of the child. For example, appropriate voice content is selected by sending a prompt sentence such as "Please recommend a story for a 3-year-old child to fall asleep calmly" to the AI.

[0307] Furthermore, the server collects feedback on the child's reaction and sleep state, and utilizes artificial intelligence to improve the accuracy of rest suggestions. As a result, the caregiver can receive individualized advice and support the child's sleep more reliably. For example, if the child finishes listening to the preferred story or music quickly, flexible responses such as adding another story are possible. Also, when the robot interacts with the child, it has a function of leading to sleep in a natural form. Thus, even when the parent is not present, the child can fall asleep with peace of mind.

[0308] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0309] Step 1:

[0310] The user inputs the individual information of the child via the terminal. The information input is age, daily rhythm, preferences before going to bed, etc. These data are sent to the server.

[0311] Step 2:

[0312] Based on the individual information it receives, the server uses a generative AI model to calculate the ideal rest time. To analyze the input data, the server considers age and daily rhythm to calculate the optimal bedtime. The calculation result is output as a recommended bedtime.

[0313] Step 3:

[0314] The server selects audio content. Using a generative AI model, it takes the prompt "Please recommend audio content to help children fall asleep" as input and selects suitable music or stories. This process outputs audio content that has a relaxing effect on children.

[0315] Step 4:

[0316] The server works in conjunction with childcare equipment to automatically optimize the child's sleep environment. The server sends instructions to smart home devices that control lighting and temperature, and based on the optimal environmental conditions obtained as input, it produces outputs such as dimming the lights or adjusting the temperature.

[0317] Step 5:

[0318] The server collects feedback on the child's responses and resting state during sleep. This feedback is collected as input from sensor devices and analyzed by the server. The analysis results are used to output data to improve the accuracy of rest suggestions.

[0319] Step 6:

[0320] The server provides personalized advice to parents. Based on the analysis results, the server generates specific advice on "timing of physical contact" and "methods of conversation" and notifies parents via message. This advice notification is the output.

[0321] Step 7:

[0322] The robot utilizes its conversational capabilities to naturally guide children to sleep. It plays audio content selected by the server, creating a relaxing environment through communication with the child. At this stage, the output is to guide the child to fall asleep peacefully.

[0323] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0324] This invention describes a form of a child sleep support system that incorporates an emotion engine that analyzes the user's emotions in real time. In addition to conventional sleep habit support, this system also takes into account the emotional state of the parents, thereby providing a more effective and personalized sleep environment.

[0325] The user enters the child's basic information into the device and sets their daily sleep patterns. The device sends this data to the server. Based on the received information, the server uses AI to calculate the optimal bedtime and analyzes the user's emotional data using an emotion engine.

[0326] The emotion engine analyzes the user's emotional state in real time based on their voice tone, facial expressions, and other factors. Based on this analysis, the server selects music and stories that are more suitable for the child and sends instructions to the home smart device to adjust the sleep environment as needed.

[0327] For example, if the server detects that the user is feeling fatigued or stressed, it will select relaxing music or short stories. It will then provide advice to the parent through the device, such as "tell a short story in a slow, gentle voice." It may also dim the room lights to create a calming environment.

[0328] Furthermore, after the bedtime process is successful, the user provides feedback via their device. This information is also analyzed on the server and used to improve the AI ​​algorithm. This allows the system to be continuously optimized and provide support tailored to individual home environments.

[0329] In this way, the present invention efficiently supports sleep habits that are suitable for individual children and parents by taking into account the emotional state of the user.

[0330] The following describes the processing flow.

[0331] Step 1:

[0332] The user launches the application on their device and enters information such as the child's age, normal sleep schedule, and preferred bedtime content. This prepares the system for setting up an individual sleep plan.

[0333] Step 2:

[0334] The device sends the data entered by the user to the server. The server receives this data and, at the user's request, uses an AI algorithm to calculate the optimal bedtime for the child.

[0335] Step 3:

[0336] The device is equipped with a mechanism to capture the user's voice and video, which is used to record the user's emotional state in real time. The emotion engine analyzes the user's voice tone and facial expressions.

[0337] Step 4:

[0338] The server receives the user's emotional data, analyzed by the emotion engine, and selects the most suitable music and stories for the child. These options are then sent to the device and presented to the child.

[0339] Step 5:

[0340] As bedtime approaches, the server sends instructions to smart devices in the home, such as adjusting the lighting and managing the temperature, to automatically create the most suitable sleep environment for the child.

[0341] Step 6:

[0342] The device plays content sent from the server and simultaneously notifies the user of advice based on the analysis results. For example, it might suggest actions such as "Take a deep breath and speak gently to your child."

[0343] Step 7:

[0344] After bedtime, users provide feedback via their device regarding their child's sleep onset and quality. The device sends this feedback to a server, which then uses the feedback to improve the AI ​​model.

[0345] Step 8:

[0346] Based on feedback and sentiment data, the server further personalizes future suggestions, continuously improving the overall effectiveness of the system.

[0347] (Example 2)

[0348] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0349] Sleep deprivation among children and parental stress are serious problems in modern society. In particular, there is a lack of sleep support methods tailored to each child's individual needs, and support that considers the impact of parental emotional state on a child's sleep is insufficient. Furthermore, there is a need to dynamically adjust the sleep environment so that parents can easily provide optimal care according to their child's condition.

[0350] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0351] In this invention, the server includes means for analyzing the parent's emotional state and providing sleep support information based on that state, means for calculating the optimal bedtime based on the child's age and lifestyle patterns, and means for coordinating with home appliances to automatically adjust the child's sleep environment. This enables personalized sleep support that takes the parent's emotional state into account, and dynamic adjustment of the sleep environment according to the child's daily rhythm.

[0352] "Analyzing a parent's emotional state" refers to using data such as the tone of their voice and facial expressions to evaluate their emotional state in real time.

[0353] "Providing sleep support information" refers to the act of offering parents specific advice, selected music, or stories to promote their children's sleep.

[0354] "Calculating the optimal bedtime" means determining the most appropriate bedtime for a given day based on the child's age and lifestyle.

[0355] "Automatically adjusting the sleep environment" refers to the process of adjusting elements such as volume, lighting, and temperature in conjunction with household devices to create an optimal sleep environment.

[0356] "Household appliances" refer to devices installed in the home, including smart devices, such as music players, lighting, and speakers.

[0357] "Artificial intelligence" refers to a technology that analyzes large amounts of data and performs advanced reasoning and learning based on the results, contributing to improving the accuracy of sleep recommendations.

[0358] "Providing an interface" refers to providing a user interface or device that allows parents to input information about their children and to recognize the parents' emotional state.

[0359] This invention is a system that supports children's sleep and provides personalized services that take into account the emotional state of the parents. First, the user inputs basic information about the child, such as age and lifestyle patterns, using a terminal. The terminal sends this data to a server. Based on the received information, the server operates a generating AI model to calculate the optimal bedtime. The AI ​​model refers to past sleep data and generates advice tailored to the individual's lifestyle rhythm.

[0360] The server also uses an emotion engine to analyze the user's voice tone and facial expressions in real time. This allows for the provision of detailed support information based on the parent's emotional state. For example, if the parent is feeling stressed or fatigued, relaxing music or stories will be selected to help the child fall asleep more easily.

[0361] Smart speakers and smart lighting are used to integrate with home appliances. The server sends instructions to these devices to play music or adjust lighting. This automatically optimizes the child's sleep environment. Furthermore, parents can provide feedback from their devices, and this information is used by the server to improve the AI ​​model, thereby increasing the accuracy of future suggestions.

[0362] For example, if a user enters "Please suggest a list of music that will help my child relax" into their device, the server uses an AI model to generate a list and plays it through a smart speaker. In this way, the system supports children and parents in enjoying a better bedtime environment.

[0363] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0364] Step 1:

[0365] Users input basic information about their child and their daily sleep patterns through their device. This information includes the child's age, typical bedtime and wake-up times, and daytime activities. This information is stored in a database and prepared for transmission to the server.

[0366] Step 2:

[0367] The terminal encrypts the information entered by the user and sends it to the server. The server stores the received data in a database and verifies the integrity of the information. A data check is performed here to check for missing values ​​or inconsistencies.

[0368] Step 3:

[0369] The server runs an AI model based on the child's information to calculate the optimal bedtime. The AI ​​model also references past sleep data, combining it with the input data to generate an optimized bedtime schedule. The calculated bedtime is then sent back to the device as feedback from the server.

[0370] Step 4:

[0371] The server uses an emotion engine to analyze the user's voice tone and facial expressions. When the user inputs audio or video into the device, their emotional state is evaluated in real time. Based on this analysis, sleep support information tailored to the parent's emotional state is generated.

[0372] Step 5:

[0373] Based on the analysis results, the server works in conjunction with home devices to select suitable music and stories. The selected content is played through a smart speaker, and simultaneously, the brightness of smart lighting and other settings are adjusted. This optimizes the sleep environment in real time.

[0374] Step 6:

[0375] Users provide feedback via their device about their child's behavior after bedtime and their own observations. This feedback is collected on a server and used to improve the AI ​​model. Based on the collected data, the system is programmed to automatically improve the accuracy of its suggestions.

[0376] (Application Example 2)

[0377] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0378] There is a need for effective means to provide an appropriate sleep environment that takes into account the emotional state and sleep quality of the elderly, thereby promoting individual health maintenance. Conventional technologies provide sleep support based on general patterns and do not adequately consider individual emotions or health conditions. As a result, optimal sleep support is not provided, and there is room for improvement to suit individual circumstances.

[0379] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0380] In this invention, the server includes means for calculating the optimal bedtime based on an individual's age and lifestyle, means for analyzing an individual's emotional state and providing appropriate music or stories, and means for giving instructions to optimize the environment based on the emotional analysis. This makes it possible to take into account the emotional state of elderly people and provide a sleep environment that is tailored to their individual needs.

[0381] "Age and lifestyle" refers to an individual's age and daily routine, and serves as a standard for providing care tailored to their individual health and lifestyle rhythms.

[0382] "Optimal bedtime" refers to the ideal time to start sleep to obtain adequate rest, based on an individual's health condition and daily activities.

[0383] "Emotional state" refers to an individual's emotional reactions and psychological state, which are assessed through tone of voice and facial expressions.

[0384] "Household appliances" refer to digital devices used within the home, including devices that control the environment such as lighting and sound equipment.

[0385] "Music and stories" refers to audio content selected according to an individual's mood or state, with the aim of promoting relaxation and sleep.

[0386] "Artificial intelligence" refers to a computer system that makes autonomous decisions through data analysis, prediction, optimization, and other processes.

[0387] An "interface" refers to a point of contact or method for a user to interact with a system, enabling the input and output of information.

[0388] The system that realizes this application provides an optimal sleep environment based on an individual's emotional state, age, and lifestyle. Specifically, it uses the following hardware and software.

[0389] The server calculates the appropriate bedtime based on an individual's age, lifestyle, and past response data. It receives data transmitted by the user via devices such as smart glasses or smartphones, and this data is analyzed by an AI algorithm. Using technologies such as the Google Cloud Vision API to analyze facial expressions captured by a camera and Amazon Polly to analyze audio data, the system selects the most suitable music and stories to create a relaxation environment tailored to the individual's physical and mental state.

[0390] Users receive environmental instructions and advice via their devices and adjust their actual environment using smart glasses and audio equipment. Lighting and music are automatically optimized, allowing individuals to naturally relax and fall asleep.

[0391] For example, if an elderly person feels anxious, the system will execute instructions such as "play relaxing music and dim the lamps" based on the analyzed data. A specific example of a prompt would be, "Please tell me how to infer emotions from an elderly person's voice and facial expression data and suggest relaxing music and environmental adjustments." This system enables flexible sleep support tailored to individual needs.

[0392] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0393] Step 1:

[0394] The user captures their personal facial expressions and voice using the camera and microphone through smart glasses and sends the data to the device. The input data consists of facial image data and audio data. The device then prepares to send this data to the server.

[0395] Step 2:

[0396] The server analyzes the received facial expression data using the Google Cloud Vision API to determine the individual's emotional state. The input is image data of facial expressions, and the output is a judgment of the emotional state (e.g., relaxed, anxious, stressed). This analysis determines the requirements for the next content to be provided.

[0397] Step 3:

[0398] The audio data is analyzed using Amazon Polly or similar voice analysis technologies to determine the tone of the voice. The input is audio data, and the output is the analysis results regarding emotional nuances and states. The server uses these results to determine the individual's current psychological state.

[0399] Step 4:

[0400] The server selects music or stories best suited to the individual based on the analysis results. This selection process utilizes music service APIs such as Pandora. The input is the result of the emotional state assessment, and the output is data of the selected music or story.

[0401] Step 5:

[0402] The system sends specific instructions regarding lighting and music to the user's device. Based on these instructions, the device controls household appliances (such as smart lights and speakers) to optimize the environment. The input is the instructions from the server, and the output is the adjusted indoor environment.

[0403] Step 6:

[0404] After going to sleep, users send feedback about their sleep status and satisfaction level from their device to the server. The input is subjective feedback data from the user, and the output is data used to train and improve the AI ​​model. The server analyzes this feedback and uses it to improve the accuracy of future service delivery.

[0405] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0406] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0407] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0408] [Third Embodiment]

[0409] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0410] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0411] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0412] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0413] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0414] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0415] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0416] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0417] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0418] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0419] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0420] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0421] This invention presents an embodiment of a system that suggests an optimal bedtime based on a child's age and current sleep schedule, and supports bedtime routines. The system begins with the user inputting basic information about the child via a terminal, and the server uses this information to select an individually optimized bedtime along with content effective for bedtime. This reduces the burden on parents while simultaneously helping children develop regular sleep habits.

[0422] The device first provides an interface for the user to input basic information about the child, such as age, daily routine, and bedtime preferences. Next, the device sends this data to the server and instructs it to process it.

[0423] The server analyzes the received data. Based on age and previous data, an AI algorithm calculates the most suitable bedtime for the child. Furthermore, it automatically selects the most suitable music or stories to promote relaxation before bedtime and instructs the device to play them. Through these processes, the server creates an environment that naturally lulls the child to sleep. The server also works in conjunction with the home's smart devices to automatically adjust the room lighting and temperature to a state suitable for sleep.

[0424] Furthermore, the server collects and analyzes sleep data, taking past history into consideration, and notifies parents with specific advice on body language and verbal cues tailored to each child. This allows parents to get their children to sleep using a more effective approach.

[0425] For example, in a family with a three-year-old child, if the child is having more trouble falling asleep than usual, the server will adjust the usual bedtime based on the child's past sleep data and current situation, and select calming music. It will then provide specific advice to the parents, such as "gently stroke their back and speak to them in a calm voice," supporting a more natural approach to putting the child to sleep.

[0426] This system allows for flexible adaptation to seasonal changes and shifts in daily routines, making it possible to continuously manage and improve children's sleep.

[0427] The following describes the processing flow.

[0428] Step 1:

[0429] The user accesses a dedicated app on their device and enters basic information such as the child's age, usual wake-up time, and preferred types of bedtime music or stories. The device then sends this data to the server.

[0430] Step 2:

[0431] The server inputs the child's basic information into an AI algorithm and calculates the optimal bedtime based on the child's age and daily routine. The server then sends this result to the device.

[0432] Step 3:

[0433] The device notifies the user of the optimal bedtime received from the server. The user can review the information and make adjustments as needed.

[0434] Step 4:

[0435] As bedtime approaches, the server uses AI to select music and stories tailored to the child's age and preferences. The server then sends this selection to the device and instructs it to begin playback.

[0436] Step 5:

[0437] The device plays selected music or stories based on instructions from the server, helping the child relax.

[0438] Step 6:

[0439] The server connects with smart devices in the home (such as smart lights and air conditioners) and automatically adjusts lighting and temperature settings to create a suitable sleep environment for children.

[0440] Step 7:

[0441] The server monitors and analyzes children's sleep data in real time and sends specific advice to the user's device regarding optimal physical contact and verbal communication.

[0442] Step 8:

[0443] The server sends a reminder to the user via the device a little before bedtime, encouraging the child to prepare for bed smoothly.

[0444] Step 9:

[0445] The user enters feedback on the child's sleep quality and bedtime process into the device. The device then sends this information to the server.

[0446] Step 10:

[0447] The server incorporates user feedback to continuously improve its AI model and enhance the accuracy of future suggestions and support.

[0448] (Example 1)

[0449] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0450] In today's busy lifestyle, many parents find it difficult to properly manage their children's sleep habits, resulting in situations where children don't get enough sleep. In particular, setting appropriate bedtimes and adjusting the sleep environment to suit each individual child is challenging, highlighting the need for support to ensure children get consistent sleep. Furthermore, parents have limited opportunities to learn effective methods for getting their children to sleep.

[0451] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0452] In this invention, the server includes means for calculating the optimal bedtime based on the child's age and daily activities, means for coordinating with a home control device to automatically adjust the child's sleeping environment, and means for automatically selecting and providing audio and video content effective for the child's pre-sleep activities. This makes it possible for each household to receive sleep support optimized for each individual child.

[0453] "Child's age" refers to the number of years calculated from the child's date of birth, which is fundamental information for optimizing sleep.

[0454] "Daily activities" refer to the typical behaviors and routines that children engage in on a daily basis, and these influence the calculation of bedtime.

[0455] "Optimal bedtime" refers to the time a child should fall asleep, calculated based on scientific evidence to support a child's healthy sleep patterns.

[0456] A "household control device" is an electronic device used to manage and adjust environmental elements such as lighting and temperature within the home.

[0457] "Sleep environment" refers to all the physical and sensory environmental elements that need to be prepared for a child to sleep comfortably.

[0458] "Audio and video" refers to sound and visual content used to promote relaxation and sleep in children.

[0459] "Parent" is a general term for guardians who are involved in raising children and who need to manage their bedtime habits.

[0460] A "user interface" refers to the screens and input devices that parents use to input information about their children and to operate services.

[0461] This invention is a system that supports the formation of optimal sleep habits based on a child's age and daily activities. The system mainly consists of a terminal, a server, and a home control unit.

[0462] The devices used by users are mobile devices such as smartphones and tablets, and a user interface is provided for parents to input basic information about their children. Parents input their child's age, daily activity information, and bedtime preferences through the device.

[0463] The information collected by the device is sent to a server via the internet. The server receives this data and uses an AI algorithm to calculate the optimal bedtime. This AI model has the ability to analyze large amounts of sleep data and extract appropriate patterns.

[0464] The server also works in conjunction with the home control system to automatically adjust the room lighting and temperature, creating an environment suitable for sleep. The selected audio and video content promotes relaxation in children and supports smooth sleep.

[0465] As a concrete example, when a user enters information about a 3-year-old child, the server uses that data to compare it with past cases and suggests an appropriate bedtime. Furthermore, it adjusts the room environment through a home control device and starts playing relaxing stories or music from the device.

[0466] An example of a prompt message is: "If a 3-year-old child has trouble falling asleep, please provide specific instructions on how to select an appropriate bedtime and music based on past sleep data, and what kind of sleep-training advice to offer the parents. Furthermore, please explain how to use smart devices to create an ideal bedroom environment."

[0467] This system allows parents to efficiently manage their children's sleep and receive support in establishing a better daily routine.

[0468] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0469] Step 1:

[0470] The user enters basic information about their child into the device. Specifically, the user enters information such as the child's age, daily routine, and bedtime preferences through the interface. This information is used as basic data for the system to calculate the optimal bedtime. The entered data is encrypted and sent to the server.

[0471] Step 2:

[0472] The terminal sends input information to the server. The terminal sends data received from the user to the server in real time. The transmitted information is stored in the server's database and prepared for analysis by AI algorithms.

[0473] Step 3:

[0474] The server analyzes the data to calculate the optimal bedtime. The AI ​​model within the server references the received data (age, activity patterns, etc.) to determine the optimal bedtime. This analysis utilizes historical statistical data and scientific research findings. As a result, a personalized bedtime is calculated for each individual child.

[0475] Step 4:

[0476] The server selects the most suitable content and issues instructions to the device. Based on the calculated bedtime, the server uses an AI algorithm to select audio and video content to help the child relax. The selected content is notified to the device, informing the user that it is ready for playback.

[0477] Step 5:

[0478] The server issues instructions to the home control unit to adjust the environment. The server communicates with smart home devices and issues commands to change the room lighting to a warmer color and adjust the temperature according to the designated bedtime. This automatically creates an optimal environment for sleeping.

[0479] Step 6:

[0480] The server provides users with specific advice on getting their children to sleep. The server sends notifications to the user's device, displaying specific advice to help with getting the child to sleep. This advice is generated based on past data analysis and the current situation. This allows parents to support effective bedtime routines.

[0481] Step 7:

[0482] The server collects sleep data and uses it for subsequent analysis. The server collects data on the child's sleep patterns from devices and home sensors. This data is used to optimize bedtimes and generate advice for future sessions, thereby enabling continuous improvement.

[0483] (Application Example 1)

[0484] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0485] Setting and achieving ideal rest schedules for children is a major challenge for parents. In particular, there is a lack of customized suggestions based on individual child information, highlighting the need for effective ways to support children in falling asleep naturally. Furthermore, existing methods are insufficient in providing appropriate feedback on children's reactions and conditions to deliver highly accurate sleep suggestions.

[0486] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0487] In this invention, the server includes means for calculating an ideal rest period based on the child's individual information and daily rhythm; means for automatically adjusting the child's sleep environment in interaction with childcare equipment; and means for providing a function for a robot to naturally guide the child to sleep while interacting with them. This enables personalized support to help children get regular rest and reduces the burden on parents.

[0488] "Individualized information" refers to specific data about an individual child, including their age, daily activities, and bedtime preferences.

[0489] "Daily routine" refers to the patterns and schedules of daily life that a child usually follows.

[0490] "Ideal rest time" refers to the recommended bedtime to ensure the most beneficial amount of sleep for a child's health and growth.

[0491] "Child development equipment" refers to electronic devices and systems used within the home to support a child's development and daily life.

[0492] A "sleep environment" refers to the totality of physical conditions such as lighting, temperature, and sound in a room that are arranged to allow a child to sleep comfortably.

[0493] "Audio content" refers to sound information such as music and stories used to promote relaxation and sleepiness in children.

[0494] "Response and rest state feedback" refers to the collection of information about a child's behavior and sleep quality, and the system's suggestions for improvement based on that information.

[0495] Artificial intelligence is a computer technology that uses programmed algorithms to understand problems and generate solutions in a way that is similar to humans.

[0496] The "function to naturally induce sleep through dialogue" refers to the ability of a robot to communicate with a child while creating an environment conducive to falling asleep.

[0497] This system aims to help children set their ideal rest schedule and support the process. The server receives individual information about the child from the user, such as age, daily routine, and bedtime preferences, and uses this information to calculate the optimal rest time. Furthermore, the server works in conjunction with childcare equipment to automatically optimize the child's sleep environment. Specifically, it controls smart home devices to optimize lighting and temperature.

[0498] The server also uses a generative AI model to analyze and select audio content suitable for children. This content includes music and stories designed to help children relax. For example, by sending a prompt such as, "Please recommend stories to help a 3-year-old child calm down and fall asleep," the AI ​​will select appropriate audio content.

[0499] Furthermore, the server collects feedback on the child's reactions and sleep patterns, and uses artificial intelligence to improve the accuracy of rest suggestions. This allows parents to receive personalized advice and more effectively support their child's sleep. For example, it can flexibly respond by adding another story if the child finishes listening to their favorite story or music too quickly. The robot also has a function to naturally guide the child to sleep when interacting with them. This allows children to fall asleep peacefully even when their parents are not present.

[0500] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0501] Step 1:

[0502] The user enters individual information about their child via a device. This information includes age, daily routine, and bedtime preferences. This data is then sent to the server.

[0503] Step 2:

[0504] Based on the individual information it receives, the server uses a generative AI model to calculate the ideal rest time. To analyze the input data, the server considers age and daily rhythm to calculate the optimal bedtime. The calculation result is output as a recommended bedtime.

[0505] Step 3:

[0506] The server selects audio content. Using a generative AI model, it takes the prompt "Please recommend audio content to help children fall asleep" as input and selects suitable music or stories. This process outputs audio content that has a relaxing effect on children.

[0507] Step 4:

[0508] The server works in conjunction with childcare equipment to automatically optimize the child's sleep environment. The server sends instructions to smart home devices that control lighting and temperature, and based on the optimal environmental conditions obtained as input, it produces outputs such as dimming the lights or adjusting the temperature.

[0509] Step 5:

[0510] The server collects feedback on the child's responses and resting state during sleep. This feedback is collected as input from sensor devices and analyzed by the server. The analysis results are used to output data to improve the accuracy of rest suggestions.

[0511] Step 6:

[0512] The server provides personalized advice to parents. Based on the analysis results, the server generates specific advice on "timing of physical contact" and "methods of conversation" and notifies parents via message. This advice notification is the output.

[0513] Step 7:

[0514] The robot utilizes its conversational capabilities to naturally guide children to sleep. It plays audio content selected by the server, creating a relaxing environment through communication with the child. At this stage, the output is to guide the child to fall asleep peacefully.

[0515] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0516] This invention describes a form of a child sleep support system that incorporates an emotion engine that analyzes the user's emotions in real time. In addition to conventional sleep habit support, this system also takes into account the emotional state of the parents, thereby providing a more effective and personalized sleep environment.

[0517] The user enters the child's basic information into the device and sets their daily sleep patterns. The device sends this data to the server. Based on the received information, the server uses AI to calculate the optimal bedtime and analyzes the user's emotional data using an emotion engine.

[0518] The emotion engine analyzes the user's emotional state in real time based on their voice tone, facial expressions, and other factors. Based on this analysis, the server selects music and stories that are more suitable for the child and sends instructions to the home smart device to adjust the sleep environment as needed.

[0519] For example, if the server detects that the user is feeling fatigued or stressed, it will select relaxing music or short stories. It will then provide advice to the parent through the device, such as "tell a short story in a slow, gentle voice." It may also dim the room lights to create a calming environment.

[0520] Furthermore, after the bedtime process is successful, the user provides feedback via their device. This information is also analyzed on the server and used to improve the AI ​​algorithm. This allows the system to be continuously optimized and provide support tailored to individual home environments.

[0521] In this way, the present invention efficiently supports sleep habits that are suitable for individual children and parents by taking into account the emotional state of the user.

[0522] The following describes the processing flow.

[0523] Step 1:

[0524] The user launches the application on their device and enters information such as the child's age, normal sleep schedule, and preferred bedtime content. This prepares the system for setting up an individual sleep plan.

[0525] Step 2:

[0526] The device sends the data entered by the user to the server. The server receives this data and, at the user's request, uses an AI algorithm to calculate the optimal bedtime for the child.

[0527] Step 3:

[0528] The device is equipped with a mechanism to capture the user's voice and video, which is used to record the user's emotional state in real time. The emotion engine analyzes the user's voice tone and facial expressions.

[0529] Step 4:

[0530] The server receives the user's emotional data, analyzed by the emotion engine, and selects the most suitable music and stories for the child. These options are then sent to the device and presented to the child.

[0531] Step 5:

[0532] As bedtime approaches, the server sends instructions to smart devices in the home, such as adjusting the lighting and managing the temperature, to automatically create the most suitable sleep environment for the child.

[0533] Step 6:

[0534] The device plays content sent from the server and simultaneously notifies the user of advice based on the analysis results. For example, it might suggest actions such as "Take a deep breath and speak gently to your child."

[0535] Step 7:

[0536] After bedtime, users provide feedback via their device regarding their child's sleep onset and quality. The device sends this feedback to a server, which then uses the feedback to improve the AI ​​model.

[0537] Step 8:

[0538] Based on feedback and sentiment data, the server further personalizes future suggestions, continuously improving the overall effectiveness of the system.

[0539] (Example 2)

[0540] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0541] Sleep deprivation among children and parental stress are serious problems in modern society. In particular, there is a lack of sleep support methods tailored to each child's individual needs, and support that considers the impact of parental emotional state on a child's sleep is insufficient. Furthermore, there is a need to dynamically adjust the sleep environment so that parents can easily provide optimal care according to their child's condition.

[0542] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0543] In this invention, the server includes means for analyzing the parent's emotional state and providing sleep support information based on that state, means for calculating the optimal bedtime based on the child's age and lifestyle patterns, and means for coordinating with home appliances to automatically adjust the child's sleep environment. This enables personalized sleep support that takes the parent's emotional state into account, and dynamic adjustment of the sleep environment according to the child's daily rhythm.

[0544] "Analyzing a parent's emotional state" refers to using data such as the tone of their voice and facial expressions to evaluate their emotional state in real time.

[0545] "Providing sleep support information" refers to the act of offering parents specific advice, selected music, or stories to promote their children's sleep.

[0546] "Calculating the optimal bedtime" means determining the most appropriate bedtime for a given day based on the child's age and lifestyle.

[0547] "Automatically adjusting the sleep environment" refers to the process of adjusting elements such as volume, lighting, and temperature in conjunction with household devices to create an optimal sleep environment.

[0548] "Household appliances" refer to devices installed in the home, including smart devices, such as music players, lighting, and speakers.

[0549] "Artificial intelligence" refers to a technology that analyzes large amounts of data and performs advanced reasoning and learning based on the results, contributing to improving the accuracy of sleep recommendations.

[0550] "Providing an interface" refers to providing a user interface or device that allows parents to input information about their children and to recognize the parents' emotional state.

[0551] This invention is a system that supports children's sleep and provides personalized services that take into account the emotional state of the parents. First, the user inputs basic information about the child, such as age and lifestyle patterns, using a terminal. The terminal sends this data to a server. Based on the received information, the server operates a generating AI model to calculate the optimal bedtime. The AI ​​model refers to past sleep data and generates advice tailored to the individual's lifestyle rhythm.

[0552] The server also uses an emotion engine to analyze the user's voice tone and facial expressions in real time. This allows for the provision of detailed support information based on the parent's emotional state. For example, if the parent is feeling stressed or fatigued, relaxing music or stories will be selected to help the child fall asleep more easily.

[0553] Smart speakers and smart lighting are used to integrate with home appliances. The server sends instructions to these devices to play music or adjust lighting. This automatically optimizes the child's sleep environment. Furthermore, parents can provide feedback from their devices, and this information is used by the server to improve the AI ​​model, thereby increasing the accuracy of future suggestions.

[0554] For example, if a user enters "Please suggest a list of music that will help my child relax" into their device, the server uses an AI model to generate a list and plays it through a smart speaker. In this way, the system supports children and parents in enjoying a better bedtime environment.

[0555] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0556] Step 1:

[0557] Users input basic information about their child and their daily sleep patterns through their device. This information includes the child's age, typical bedtime and wake-up times, and daytime activities. This information is stored in a database and prepared for transmission to the server.

[0558] Step 2:

[0559] The terminal encrypts the information entered by the user and sends it to the server. The server stores the received data in a database and verifies the integrity of the information. A data check is performed here to check for missing values ​​or inconsistencies.

[0560] Step 3:

[0561] The server runs an AI model based on the child's information to calculate the optimal bedtime. The AI ​​model also references past sleep data, combining it with the input data to generate an optimized bedtime schedule. The calculated bedtime is then sent back to the device as feedback from the server.

[0562] Step 4:

[0563] The server uses an emotion engine to analyze the user's voice tone and facial expressions. When the user inputs audio or video into the device, their emotional state is evaluated in real time. Based on this analysis, sleep support information tailored to the parent's emotional state is generated.

[0564] Step 5:

[0565] Based on the analysis results, the server works in conjunction with home devices to select suitable music and stories. The selected content is played through a smart speaker, and simultaneously, the brightness of smart lighting and other settings are adjusted. This optimizes the sleep environment in real time.

[0566] Step 6:

[0567] Users provide feedback via their device about their child's behavior after bedtime and their own observations. This feedback is collected on a server and used to improve the AI ​​model. Based on the collected data, the system is programmed to automatically improve the accuracy of its suggestions.

[0568] (Application Example 2)

[0569] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0570] There is a need for effective means to provide an appropriate sleep environment that takes into account the emotional state and sleep quality of the elderly, thereby promoting individual health maintenance. Conventional technologies provide sleep support based on general patterns and do not adequately consider individual emotions or health conditions. As a result, optimal sleep support is not provided, and there is room for improvement to suit individual circumstances.

[0571] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0572] In this invention, the server includes means for calculating the optimal bedtime based on an individual's age and lifestyle, means for analyzing an individual's emotional state and providing appropriate music or stories, and means for giving instructions to optimize the environment based on the emotional analysis. This makes it possible to take into account the emotional state of elderly people and provide a sleep environment that is tailored to their individual needs.

[0573] "Age and lifestyle" refers to an individual's age and daily routine, and serves as a standard for providing care tailored to their individual health and lifestyle rhythms.

[0574] "Optimal bedtime" refers to the ideal time to start sleep to obtain adequate rest, based on an individual's health condition and daily activities.

[0575] "Emotional state" refers to an individual's emotional reactions and psychological state, which are assessed through tone of voice and facial expressions.

[0576] "Household appliances" refer to digital devices used within the home, including devices that control the environment such as lighting and sound equipment.

[0577] "Music and stories" refers to audio content selected according to an individual's mood or state, with the aim of promoting relaxation and sleep.

[0578] "Artificial intelligence" refers to a computer system that makes autonomous decisions through data analysis, prediction, optimization, and other processes.

[0579] An "interface" refers to a point of contact or method for a user to interact with a system, enabling the input and output of information.

[0580] The system that realizes this application provides an optimal sleep environment based on an individual's emotional state, age, and lifestyle. Specifically, it uses the following hardware and software.

[0581] The server calculates the appropriate bedtime based on an individual's age, lifestyle, and past response data. It receives data transmitted by the user via devices such as smart glasses or smartphones, and this data is analyzed by an AI algorithm. Using technologies such as the Google Cloud Vision API to analyze facial expressions captured by a camera and Amazon Polly to analyze audio data, the system selects the most suitable music and stories to create a relaxation environment tailored to the individual's physical and mental state.

[0582] Users receive environmental instructions and advice via their devices and adjust their actual environment using smart glasses and audio equipment. Lighting and music are automatically optimized, allowing individuals to naturally relax and fall asleep.

[0583] For example, if an elderly person feels anxious, the system will execute instructions such as "play relaxing music and dim the lamps" based on the analyzed data. A specific example of a prompt would be, "Please tell me how to infer emotions from an elderly person's voice and facial expression data and suggest relaxing music and environmental adjustments." This system enables flexible sleep support tailored to individual needs.

[0584] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0585] Step 1:

[0586] The user captures their personal facial expressions and voice using the camera and microphone through smart glasses and sends the data to the device. The input data consists of facial image data and audio data. The device then prepares to send this data to the server.

[0587] Step 2:

[0588] The server analyzes the received facial expression data using the Google Cloud Vision API to determine the individual's emotional state. The input is image data of facial expressions, and the output is a judgment of the emotional state (e.g., relaxed, anxious, stressed). This analysis determines the requirements for the next content to be provided.

[0589] Step 3:

[0590] The audio data is analyzed using Amazon Polly or similar voice analysis technologies to determine the tone of the voice. The input is audio data, and the output is the analysis results regarding emotional nuances and states. The server uses these results to determine the individual's current psychological state.

[0591] Step 4:

[0592] The server selects music or stories best suited to the individual based on the analysis results. This selection process utilizes music service APIs such as Pandora. The input is the result of the emotional state assessment, and the output is data of the selected music or story.

[0593] Step 5:

[0594] The system sends specific instructions regarding lighting and music to the user's device. Based on these instructions, the device controls household appliances (such as smart lights and speakers) to optimize the environment. The input is the instructions from the server, and the output is the adjusted indoor environment.

[0595] Step 6:

[0596] After going to sleep, users send feedback about their sleep status and satisfaction level from their device to the server. The input is subjective feedback data from the user, and the output is data used to train and improve the AI ​​model. The server analyzes this feedback and uses it to improve the accuracy of future service delivery.

[0597] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0598] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0599] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0600] [Fourth Embodiment]

[0601] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0602] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0603] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0604] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0605] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0606] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0607] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0608] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0609] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0610] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0611] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0612] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0613] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0614] This invention presents an embodiment of a system that suggests an optimal bedtime based on a child's age and current sleep schedule, and supports bedtime routines. The system begins with the user inputting basic information about the child via a terminal, and the server uses this information to select an individually optimized bedtime along with content effective for bedtime. This reduces the burden on parents while simultaneously helping children develop regular sleep habits.

[0615] The device first provides an interface for the user to input basic information about the child, such as age, daily routine, and bedtime preferences. Next, the device sends this data to the server and instructs it to process it.

[0616] The server analyzes the received data. Based on age and previous data, an AI algorithm calculates the most suitable bedtime for the child. Furthermore, it automatically selects the most suitable music or stories to promote relaxation before bedtime and instructs the device to play them. Through these processes, the server creates an environment that naturally lulls the child to sleep. The server also works in conjunction with the home's smart devices to automatically adjust the room lighting and temperature to a state suitable for sleep.

[0617] Furthermore, the server collects and analyzes sleep data, taking past history into consideration, and notifies parents with specific advice on body language and verbal cues tailored to each child. This allows parents to get their children to sleep using a more effective approach.

[0618] For example, in a family with a three-year-old child, if the child is having more trouble falling asleep than usual, the server will adjust the usual bedtime based on the child's past sleep data and current situation, and select calming music. It will then provide specific advice to the parents, such as "gently stroke their back and speak to them in a calm voice," supporting a more natural approach to putting the child to sleep.

[0619] This system allows for flexible adaptation to seasonal changes and shifts in daily routines, making it possible to continuously manage and improve children's sleep.

[0620] The following describes the processing flow.

[0621] Step 1:

[0622] The user accesses a dedicated app on their device and enters basic information such as the child's age, usual wake-up time, and preferred types of bedtime music or stories. The device then sends this data to the server.

[0623] Step 2:

[0624] The server inputs the child's basic information into an AI algorithm and calculates the optimal bedtime based on the child's age and daily routine. The server then sends this result to the device.

[0625] Step 3:

[0626] The device notifies the user of the optimal bedtime received from the server. The user can review the information and make adjustments as needed.

[0627] Step 4:

[0628] As bedtime approaches, the server uses AI to select music and stories tailored to the child's age and preferences. The server then sends this selection to the device and instructs it to begin playback.

[0629] Step 5:

[0630] The device plays selected music or stories based on instructions from the server, helping the child relax.

[0631] Step 6:

[0632] The server connects with smart devices in the home (such as smart lights and air conditioners) and automatically adjusts lighting and temperature settings to create a suitable sleep environment for children.

[0633] Step 7:

[0634] The server monitors and analyzes children's sleep data in real time and sends specific advice to the user's device regarding optimal physical contact and verbal communication.

[0635] Step 8:

[0636] The server sends a reminder to the user via the device a little before bedtime, encouraging the child to prepare for bed smoothly.

[0637] Step 9:

[0638] The user enters feedback on the child's sleep quality and bedtime process into the device. The device then sends this information to the server.

[0639] Step 10:

[0640] The server incorporates user feedback to continuously improve its AI model and enhance the accuracy of future suggestions and support.

[0641] (Example 1)

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

[0643] In today's busy lifestyle, many parents find it difficult to properly manage their children's sleep habits, resulting in situations where children don't get enough sleep. In particular, setting appropriate bedtimes and adjusting the sleep environment to suit each individual child is challenging, highlighting the need for support to ensure children get consistent sleep. Furthermore, parents have limited opportunities to learn effective methods for getting their children to sleep.

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

[0645] In this invention, the server includes means for calculating the optimal bedtime based on the child's age and daily activities, means for coordinating with a home control device to automatically adjust the child's sleeping environment, and means for automatically selecting and providing audio and video content effective for the child's pre-sleep activities. This makes it possible for each household to receive sleep support optimized for each individual child.

[0646] "Child's age" refers to the number of years calculated from the child's date of birth, which is fundamental information for optimizing sleep.

[0647] "Daily activities" refer to the typical behaviors and routines that children engage in on a daily basis, and these influence the calculation of bedtime.

[0648] "Optimal bedtime" refers to the time a child should fall asleep, calculated based on scientific evidence to support a child's healthy sleep patterns.

[0649] A "household control device" is an electronic device used to manage and adjust environmental elements such as lighting and temperature within the home.

[0650] "Sleep environment" refers to all the physical and sensory environmental elements that need to be prepared for a child to sleep comfortably.

[0651] "Audio and video" refers to sound and visual content used to promote relaxation and sleep in children.

[0652] "Parent" is a general term for guardians who are involved in raising children and who need to manage their bedtime habits.

[0653] A "user interface" refers to the screens and input devices that parents use to input information about their children and to operate services.

[0654] This invention is a system that supports the formation of optimal sleep habits based on a child's age and daily activities. The system mainly consists of a terminal, a server, and a home control unit.

[0655] The devices used by users are mobile devices such as smartphones and tablets, and a user interface is provided for parents to input basic information about their children. Parents input their child's age, daily activity information, and bedtime preferences through the device.

[0656] The information collected by the device is sent to a server via the internet. The server receives this data and uses an AI algorithm to calculate the optimal bedtime. This AI model has the ability to analyze large amounts of sleep data and extract appropriate patterns.

[0657] The server also works in conjunction with the home control system to automatically adjust the room lighting and temperature, creating an environment suitable for sleep. The selected audio and video content promotes relaxation in children and supports smooth sleep.

[0658] As a concrete example, when a user enters information about a 3-year-old child, the server uses that data to compare it with past cases and suggests an appropriate bedtime. Furthermore, it adjusts the room environment through a home control device and starts playing relaxing stories or music from the device.

[0659] An example of a prompt message is: "If a 3-year-old child has trouble falling asleep, please provide specific instructions on how to select an appropriate bedtime and music based on past sleep data, and what kind of sleep-training advice to offer the parents. Furthermore, please explain how to use smart devices to create an ideal bedroom environment."

[0660] This system allows parents to efficiently manage their children's sleep and receive support in establishing a better daily routine.

[0661] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0662] Step 1:

[0663] The user enters basic information about their child into the device. Specifically, the user enters information such as the child's age, daily routine, and bedtime preferences through the interface. This information is used as basic data for the system to calculate the optimal bedtime. The entered data is encrypted and sent to the server.

[0664] Step 2:

[0665] The terminal sends input information to the server. The terminal sends data received from the user to the server in real time. The transmitted information is stored in the server's database and prepared for analysis by AI algorithms.

[0666] Step 3:

[0667] The server analyzes the data to calculate the optimal bedtime. The AI ​​model within the server references the received data (age, activity patterns, etc.) to determine the optimal bedtime. This analysis utilizes historical statistical data and scientific research findings. As a result, a personalized bedtime is calculated for each individual child.

[0668] Step 4:

[0669] The server selects the most suitable content and issues instructions to the device. Based on the calculated bedtime, the server uses an AI algorithm to select audio and video content to help the child relax. The selected content is notified to the device, informing the user that it is ready for playback.

[0670] Step 5:

[0671] The server issues instructions to the home control unit to adjust the environment. The server communicates with smart home devices and issues commands to change the room lighting to a warmer color and adjust the temperature according to the designated bedtime. This automatically creates an optimal environment for sleeping.

[0672] Step 6:

[0673] The server provides users with specific advice on getting their children to sleep. The server sends notifications to the user's device, displaying specific advice to help with getting the child to sleep. This advice is generated based on past data analysis and the current situation. This allows parents to support effective bedtime routines.

[0674] Step 7:

[0675] The server collects sleep data and uses it for subsequent analysis. The server collects data on the child's sleep patterns from devices and home sensors. This data is used to optimize bedtimes and generate advice for future sessions, thereby enabling continuous improvement.

[0676] (Application Example 1)

[0677] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0678] Setting and achieving ideal rest schedules for children is a major challenge for parents. In particular, there is a lack of customized suggestions based on individual child information, highlighting the need for effective ways to support children in falling asleep naturally. Furthermore, existing methods are insufficient in providing appropriate feedback on children's reactions and conditions to deliver highly accurate sleep suggestions.

[0679] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0680] In this invention, the server includes means for calculating an ideal rest period based on the child's individual information and daily rhythm; means for automatically adjusting the child's sleep environment in interaction with childcare equipment; and means for providing a function for a robot to naturally guide the child to sleep while interacting with them. This enables personalized support to help children get regular rest and reduces the burden on parents.

[0681] "Individualized information" refers to specific data about an individual child, including their age, daily activities, and bedtime preferences.

[0682] "Daily routine" refers to the patterns and schedules of daily life that a child usually follows.

[0683] "Ideal rest time" refers to the recommended bedtime to ensure the most beneficial amount of sleep for a child's health and growth.

[0684] "Child development equipment" refers to electronic devices and systems used within the home to support a child's development and daily life.

[0685] A "sleep environment" refers to the totality of physical conditions such as lighting, temperature, and sound in a room that are arranged to allow a child to sleep comfortably.

[0686] "Audio content" refers to sound information such as music and stories used to promote relaxation and sleepiness in children.

[0687] "Response and rest state feedback" refers to the collection of information about a child's behavior and sleep quality, and the system's suggestions for improvement based on that information.

[0688] Artificial intelligence is a computer technology that uses programmed algorithms to understand problems and generate solutions in a way that is similar to humans.

[0689] The "function to naturally induce sleep through dialogue" refers to the ability of a robot to communicate with a child while creating an environment conducive to falling asleep.

[0690] This system aims to help children set their ideal rest schedule and support the process. The server receives individual information about the child from the user, such as age, daily routine, and bedtime preferences, and uses this information to calculate the optimal rest time. Furthermore, the server works in conjunction with childcare equipment to automatically optimize the child's sleep environment. Specifically, it controls smart home devices to optimize lighting and temperature.

[0691] The server also uses a generative AI model to analyze and select audio content suitable for children. This content includes music and stories designed to help children relax. For example, by sending a prompt such as, "Please recommend stories to help a 3-year-old child calm down and fall asleep," the AI ​​will select appropriate audio content.

[0692] Furthermore, the server collects feedback on the child's reactions and sleep patterns, and uses artificial intelligence to improve the accuracy of rest suggestions. This allows parents to receive personalized advice and more effectively support their child's sleep. For example, it can flexibly respond by adding another story if the child finishes listening to their favorite story or music too quickly. The robot also has a function to naturally guide the child to sleep when interacting with them. This allows children to fall asleep peacefully even when their parents are not present.

[0693] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0694] Step 1:

[0695] The user enters individual information about their child via a device. This information includes age, daily routine, and bedtime preferences. This data is then sent to the server.

[0696] Step 2:

[0697] Based on the individual information it receives, the server uses a generative AI model to calculate the ideal rest time. To analyze the input data, the server considers age and daily rhythm to calculate the optimal bedtime. The calculation result is output as a recommended bedtime.

[0698] Step 3:

[0699] The server selects audio content. Using a generative AI model, it takes the prompt "Please recommend audio content to help children fall asleep" as input and selects suitable music or stories. This process outputs audio content that has a relaxing effect on children.

[0700] Step 4:

[0701] The server works in conjunction with childcare equipment to automatically optimize the child's sleep environment. The server sends instructions to smart home devices that control lighting and temperature, and based on the optimal environmental conditions obtained as input, it produces outputs such as dimming the lights or adjusting the temperature.

[0702] Step 5:

[0703] The server collects feedback on the child's responses and resting state during sleep. This feedback is collected as input from sensor devices and analyzed by the server. The analysis results are used to output data to improve the accuracy of rest suggestions.

[0704] Step 6:

[0705] The server provides personalized advice to parents. Based on the analysis results, the server generates specific advice on "timing of physical contact" and "methods of conversation" and notifies parents via message. This advice notification is the output.

[0706] Step 7:

[0707] The robot utilizes its conversational capabilities to naturally guide children to sleep. It plays audio content selected by the server, creating a relaxing environment through communication with the child. At this stage, the output is to guide the child to fall asleep peacefully.

[0708] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0709] This invention describes a form of a child sleep support system that incorporates an emotion engine that analyzes the user's emotions in real time. In addition to conventional sleep habit support, this system also takes into account the emotional state of the parents, thereby providing a more effective and personalized sleep environment.

[0710] The user enters the child's basic information into the device and sets their daily sleep patterns. The device sends this data to the server. Based on the received information, the server uses AI to calculate the optimal bedtime and analyzes the user's emotional data using an emotion engine.

[0711] The emotion engine analyzes the user's emotional state in real time based on their voice tone, facial expressions, and other factors. Based on this analysis, the server selects music and stories that are more suitable for the child and sends instructions to the home smart device to adjust the sleep environment as needed.

[0712] For example, if the server detects that the user is feeling fatigued or stressed, it will select relaxing music or short stories. It will then provide advice to the parent through the device, such as "tell a short story in a slow, gentle voice." It may also dim the room lights to create a calming environment.

[0713] Furthermore, after the bedtime process is successful, the user provides feedback via their device. This information is also analyzed on the server and used to improve the AI ​​algorithm. This allows the system to be continuously optimized and provide support tailored to individual home environments.

[0714] In this way, the present invention efficiently supports sleep habits that are suitable for individual children and parents by taking into account the emotional state of the user.

[0715] The following describes the processing flow.

[0716] Step 1:

[0717] The user launches the application on their device and enters information such as the child's age, normal sleep schedule, and preferred bedtime content. This prepares the system for setting up an individual sleep plan.

[0718] Step 2:

[0719] The device sends the data entered by the user to the server. The server receives this data and, at the user's request, uses an AI algorithm to calculate the optimal bedtime for the child.

[0720] Step 3:

[0721] The device is equipped with a mechanism to capture the user's voice and video, which is used to record the user's emotional state in real time. The emotion engine analyzes the user's voice tone and facial expressions.

[0722] Step 4:

[0723] The server receives the user's emotional data, analyzed by the emotion engine, and selects the most suitable music and stories for the child. These options are then sent to the device and presented to the child.

[0724] Step 5:

[0725] As bedtime approaches, the server sends instructions to smart devices in the home, such as adjusting the lighting and managing the temperature, to automatically create the most suitable sleep environment for the child.

[0726] Step 6:

[0727] The device plays content sent from the server and simultaneously notifies the user of advice based on the analysis results. For example, it might suggest actions such as "Take a deep breath and speak gently to your child."

[0728] Step 7:

[0729] After bedtime, users provide feedback via their device regarding their child's sleep onset and quality. The device sends this feedback to a server, which then uses the feedback to improve the AI ​​model.

[0730] Step 8:

[0731] Based on feedback and sentiment data, the server further personalizes future suggestions, continuously improving the overall effectiveness of the system.

[0732] (Example 2)

[0733] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0734] Sleep deprivation among children and parental stress are serious problems in modern society. In particular, there is a lack of sleep support methods tailored to each child's individual needs, and support that considers the impact of parental emotional state on a child's sleep is insufficient. Furthermore, there is a need to dynamically adjust the sleep environment so that parents can easily provide optimal care according to their child's condition.

[0735] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0736] In this invention, the server includes means for analyzing the parent's emotional state and providing sleep support information based on that state, means for calculating the optimal bedtime based on the child's age and lifestyle patterns, and means for coordinating with home appliances to automatically adjust the child's sleep environment. This enables personalized sleep support that takes the parent's emotional state into account, and dynamic adjustment of the sleep environment according to the child's daily rhythm.

[0737] "Analyzing a parent's emotional state" refers to using data such as the tone of their voice and facial expressions to evaluate their emotional state in real time.

[0738] "Providing sleep support information" refers to the act of offering parents specific advice, selected music, or stories to promote their children's sleep.

[0739] "Calculating the optimal bedtime" means determining the most appropriate bedtime for a given day based on the child's age and lifestyle.

[0740] "Automatically adjusting the sleep environment" refers to the process of adjusting elements such as volume, lighting, and temperature in conjunction with household devices to create an optimal sleep environment.

[0741] "Household appliances" refer to devices installed in the home, including smart devices, such as music players, lighting, and speakers.

[0742] "Artificial intelligence" refers to a technology that analyzes large amounts of data and performs advanced reasoning and learning based on the results, contributing to improving the accuracy of sleep recommendations.

[0743] "Providing an interface" refers to providing a user interface or device that allows parents to input information about their children and to recognize the parents' emotional state.

[0744] This invention is a system that supports children's sleep and provides personalized services that take into account the emotional state of the parents. First, the user inputs basic information about the child, such as age and lifestyle patterns, using a terminal. The terminal sends this data to a server. Based on the received information, the server operates a generating AI model to calculate the optimal bedtime. The AI ​​model refers to past sleep data and generates advice tailored to the individual's lifestyle rhythm.

[0745] The server also uses an emotion engine to analyze the user's voice tone and facial expressions in real time. This allows for the provision of detailed support information based on the parent's emotional state. For example, if the parent is feeling stressed or fatigued, relaxing music or stories will be selected to help the child fall asleep more easily.

[0746] Smart speakers and smart lighting are used to integrate with home appliances. The server sends instructions to these devices to play music or adjust lighting. This automatically optimizes the child's sleep environment. Furthermore, parents can provide feedback from their devices, and this information is used by the server to improve the AI ​​model, thereby increasing the accuracy of future suggestions.

[0747] For example, if a user enters "Please suggest a list of music that will help my child relax" into their device, the server uses an AI model to generate a list and plays it through a smart speaker. In this way, the system supports children and parents in enjoying a better bedtime environment.

[0748] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0749] Step 1:

[0750] Users input basic information about their child and their daily sleep patterns through their device. This information includes the child's age, typical bedtime and wake-up times, and daytime activities. This information is stored in a database and prepared for transmission to the server.

[0751] Step 2:

[0752] The terminal encrypts the information entered by the user and sends it to the server. The server stores the received data in a database and verifies the integrity of the information. A data check is performed here to check for missing values ​​or inconsistencies.

[0753] Step 3:

[0754] The server runs an AI model based on the child's information to calculate the optimal bedtime. The AI ​​model also references past sleep data, combining it with the input data to generate an optimized bedtime schedule. The calculated bedtime is then sent back to the device as feedback from the server.

[0755] Step 4:

[0756] The server uses an emotion engine to analyze the user's voice tone and facial expressions. When the user inputs audio or video into the device, their emotional state is evaluated in real time. Based on this analysis, sleep support information tailored to the parent's emotional state is generated.

[0757] Step 5:

[0758] Based on the analysis results, the server works in conjunction with home devices to select suitable music and stories. The selected content is played through a smart speaker, and simultaneously, the brightness of smart lighting and other settings are adjusted. This optimizes the sleep environment in real time.

[0759] Step 6:

[0760] Users provide feedback via their device about their child's behavior after bedtime and their own observations. This feedback is collected on a server and used to improve the AI ​​model. Based on the collected data, the system is programmed to automatically improve the accuracy of its suggestions.

[0761] (Application Example 2)

[0762] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0763] There is a need for effective means to provide an appropriate sleep environment that takes into account the emotional state and sleep quality of the elderly, thereby promoting individual health maintenance. Conventional technologies provide sleep support based on general patterns and do not adequately consider individual emotions or health conditions. As a result, optimal sleep support is not provided, and there is room for improvement to suit individual circumstances.

[0764] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0765] In this invention, the server includes means for calculating the optimal bedtime based on an individual's age and lifestyle, means for analyzing an individual's emotional state and providing appropriate music or stories, and means for giving instructions to optimize the environment based on the emotional analysis. This makes it possible to take into account the emotional state of elderly people and provide a sleep environment that is tailored to their individual needs.

[0766] "Age and lifestyle" refers to an individual's age and daily routine, and serves as a standard for providing care tailored to their individual health and lifestyle rhythms.

[0767] "Optimal bedtime" refers to the ideal time to start sleep to obtain adequate rest, based on an individual's health condition and daily activities.

[0768] "Emotional state" refers to an individual's emotional reactions and psychological state, which are assessed through tone of voice and facial expressions.

[0769] "Household appliances" refer to digital devices used within the home, including devices that control the environment such as lighting and sound equipment.

[0770] "Music and stories" refers to audio content selected according to an individual's mood or state, with the aim of promoting relaxation and sleep.

[0771] "Artificial intelligence" refers to a computer system that makes autonomous decisions through data analysis, prediction, optimization, and other processes.

[0772] An "interface" refers to a point of contact or method for a user to interact with a system, enabling the input and output of information.

[0773] The system that realizes this application provides an optimal sleep environment based on an individual's emotional state, age, and lifestyle. Specifically, it uses the following hardware and software.

[0774] The server calculates the appropriate bedtime based on an individual's age, lifestyle, and past response data. It receives data transmitted by the user via devices such as smart glasses or smartphones, and this data is analyzed by an AI algorithm. Using technologies such as the Google Cloud Vision API to analyze facial expressions captured by a camera and Amazon Polly to analyze audio data, the system selects the most suitable music and stories to create a relaxation environment tailored to the individual's physical and mental state.

[0775] Users receive environmental instructions and advice via their devices and adjust their actual environment using smart glasses and audio equipment. Lighting and music are automatically optimized, allowing individuals to naturally relax and fall asleep.

[0776] For example, if an elderly person feels anxious, the system will execute instructions such as "play relaxing music and dim the lamps" based on the analyzed data. A specific example of a prompt would be, "Please tell me how to infer emotions from an elderly person's voice and facial expression data and suggest relaxing music and environmental adjustments." This system enables flexible sleep support tailored to individual needs.

[0777] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0778] Step 1:

[0779] The user captures their personal facial expressions and voice using the camera and microphone through smart glasses and sends the data to the device. The input data consists of facial image data and audio data. The device then prepares to send this data to the server.

[0780] Step 2:

[0781] The server analyzes the received facial expression data using the Google Cloud Vision API to determine the individual's emotional state. The input is image data of facial expressions, and the output is a judgment of the emotional state (e.g., relaxed, anxious, stressed). This analysis determines the requirements for the next content to be provided.

[0782] Step 3:

[0783] The audio data is analyzed using Amazon Polly or similar voice analysis technologies to determine the tone of the voice. The input is audio data, and the output is the analysis results regarding emotional nuances and states. The server uses these results to determine the individual's current psychological state.

[0784] Step 4:

[0785] The server selects music or stories best suited to the individual based on the analysis results. This selection process utilizes music service APIs such as Pandora. The input is the result of the emotional state assessment, and the output is data of the selected music or story.

[0786] Step 5:

[0787] The system sends specific instructions regarding lighting and music to the user's device. Based on these instructions, the device controls household appliances (such as smart lights and speakers) to optimize the environment. The input is the instructions from the server, and the output is the adjusted indoor environment.

[0788] Step 6:

[0789] After going to sleep, users send feedback about their sleep status and satisfaction level from their device to the server. The input is subjective feedback data from the user, and the output is data used to train and improve the AI ​​model. The server analyzes this feedback and uses it to improve the accuracy of future service delivery.

[0790] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0791] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0792] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0793] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0794] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0795] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0796] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0797] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0798] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0799] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0800] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0801] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0802] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0803] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0804] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0805] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0806] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0807] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0808] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0809] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0810] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0811] The following is further disclosed regarding the embodiments described above.

[0812] (Claim 1)

[0813] A method for calculating the optimal bedtime based on a child's age and daily routine,

[0814] To automatically adjust the child's sleep environment, a means of linking with home devices,

[0815] A method for automatically selecting and providing music and stories that are effective for getting children to sleep,

[0816] A means of analyzing children's sleep data and providing parents with advice on appropriate physical touch and verbal communication,

[0817] A way to prompt a reminder as bedtime approaches,

[0818] A system that includes this.

[0819] (Claim 2)

[0820] The system according to claim 1, comprising means of utilizing artificial intelligence to improve the accuracy of sleep suggestions and advice using feedback on the child's reactions and sleep patterns.

[0821] (Claim 3)

[0822] The system according to claim 1, comprising means for providing an interface for a parent to input information about their child.

[0823] "Example 1"

[0824] (Claim 1)

[0825] A method for calculating the optimal bedtime based on a child's age and daily activities,

[0826] A means of automatically adjusting the sleeping environment for children, in conjunction with a home control device,

[0827] A method for automatically selecting and providing audio and video content that is effective for children's bedtime activities,

[0828] A means of analyzing children's sleep information and providing parents with advice on appropriate ways to interact with and talk to them,

[0829] A means of notifying that bedtime is approaching,

[0830] Based on the information obtained through this system, we will provide a means to propose ways to offer a comfortable sleeping environment.

[0831] A system that includes this.

[0832] (Claim 2)

[0833] The system according to claim 1, comprising means of utilizing a generative AI model to improve the accuracy of bedtime suggestions and advice using feedback on the child's reactions and sleep patterns.

[0834] (Claim 3)

[0835] The system according to claim 1, comprising means for providing a user interface for a parent to input information about their child.

[0836] "Application Example 1"

[0837] (Claim 1)

[0838] A means of calculating the ideal rest time based on a child's individual information and daily rhythm,

[0839] A means of automatically adjusting a child's sleep environment by interacting with developmental equipment,

[0840] A method for automatically selecting and providing audio content and stories that are effective for children's relaxation time,

[0841] A means of analyzing a child's sleep history and providing parents with advice on physical contact and conversation tailored to each child,

[0842] A means of providing notifications as bedtime approaches,

[0843] A means to provide a function that allows a robot to naturally guide a child to sleep while interacting with them,

[0844] A system that includes this.

[0845] (Claim 2)

[0846] The system according to claim 1, comprising means of using artificial intelligence to improve the accuracy of rest suggestions and advice using feedback on the child's responses and resting state.

[0847] (Claim 3)

[0848] The system according to claim 1, comprising means for providing an interface for a parent to input individual information of a child.

[0849] "Example 2 of combining an emotion engine"

[0850] (Claim 1)

[0851] A means of analyzing the emotional state of parents and providing sleep support information based on that analysis,

[0852] A method for calculating the optimal bedtime based on a child's age and lifestyle,

[0853] To automatically adjust the child's sleep environment, a means of linking with home devices,

[0854] A method for automatically selecting and providing music and stories that are effective for getting children to sleep,

[0855] A means of analyzing children's sleep information and providing parents with advice on appropriate physical contact and verbal communication,

[0856] A way to receive a reminder notification when bedtime approaches,

[0857] A system that includes this.

[0858] (Claim 2)

[0859] The system according to claim 1, comprising means for using artificial intelligence to reflect parental feedback and improve the accuracy of sleep suggestions and advice.

[0860] (Claim 3)

[0861] The system according to claim 1, further comprising means for providing an interface for parents to input information about their children and to understand the parents' emotional state.

[0862] "Application example 2 when combining with an emotional engine"

[0863] (Claim 1)

[0864] A means for calculating the optimal bedtime based on an individual's age and lifestyle,

[0865] To automatically adjust the individual's sleep environment, a means of linking with home devices,

[0866] A means of automatically selecting and providing music and stories that are effective for putting an individual to sleep,

[0867] A means of analyzing an individual's emotional state and providing advice on appropriate body language and verbal communication,

[0868] A way to prompt a reminder as bedtime approaches,

[0869] A means of selecting appropriate music based on emotional analysis when relaxation is needed and providing instructions to optimize the environment,

[0870] A system that includes this.

[0871] (Claim 2)

[0872] The system according to claim 1, comprising means of utilizing artificial intelligence to improve the accuracy of sleep suggestions and advice using feedback on individual responses and sleep patterns.

[0873] (Claim 3)

[0874] The system according to claim 1, comprising means for providing an interface for an individual to input information. [Explanation of Symbols]

[0875] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A method for calculating the optimal bedtime based on a child's age and daily routine, To automatically adjust the child's sleep environment, a means of linking with home devices, A method for automatically selecting and providing music and stories that are effective for getting children to sleep, A means of analyzing children's sleep data and providing parents with advice on appropriate physical touch and verbal communication, A way to prompt a reminder as bedtime approaches, A system that includes this.

2. The system according to claim 1, comprising means of utilizing artificial intelligence to improve the accuracy of sleep suggestions and advice using feedback on the child's reactions and sleep patterns.

3. The system according to claim 1, comprising means for providing an interface for a parent to input information about their child.

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