System

Abstract

A system is provided.SOLUTION: The system includes means for collecting data from a terminal of a user, means for transmitting the data to a server, means for analyzing a behavior pattern of the user based on the data, means for generating a child-raising advice based on the behavior pattern analysis, and means for notifying the terminal of the user of the child-raising advice.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] The challenge is to alleviate the burden of childcare and support the harmonious development of families by resolving the anxieties and questions that new fathers face in childcare and providing specific and practical advice. Conventional information provision systems provide a lot of general information, which makes it difficult to provide appropriate advice tailored to the individual situation of the user. [Means for solving the problem]

[0005] To solve this problem, we provide a system that includes means for collecting calendar information, GPS data, information on applications used, etc. from a user's device, means for transmitting the collected data to a server, means for analyzing the user's behavioral patterns based on the collected data in the server, means for generating child-rearing advice based on the behavioral pattern analysis, and means for notifying the user's device of the generated child-rearing advice. This system provides specific child-rearing advice tailored to the user's individual situation in real time, and can alleviate any concerns or questions about child-rearing.

[0006] "User" refers to a user such as a new father who uses the system to receive child-rearing advice.

[0007] "Terminal" refers to a mobile electronic device such as a smartphone or tablet used by a user.

[0008] "Data" refers to a collection of information collected from a user's device, including calendar information, GPS data, and information about apps used.

[0009] "Server" refers to a remote computer system that receives, stores, and analyzes data sent from a user's terminal.

[0010] "Behavioral patterns" refer to specific behavioral tendencies and habits of users that are analyzed based on collected data.

[0011] "Childcare advice" refers to advice and guidance on childcare that is generated based on the results of analyzing behavioral patterns.

[0012] "Notification" refers to the act of sending childcare advice to the user's device in real time. [Brief explanation of the drawings]

[0013] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2]1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0014] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0017] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0018] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0019] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0021] [First embodiment]

[0022] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0023] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0024] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0025] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0026] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0027] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0028] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0029] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0031] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0032] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0033] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0034] This invention is a system that provides optimal child-rearing advice by eliminating the anxieties and doubts that new fathers face in child-rearing. This system uses the user's device and a server to collect and analyze data and provide specific child-rearing advice in real time.

[0035] Collecting user information

[0036] The device collects various data related to the user's behavior and environment, specifically, calendar information, GPS data, and information about the apps used, on a regular basis.

[0037] Specific examples

[0038] If a user has "Putting the child to bed (20:00)" scheduled on their smartphone calendar, the device will detect this information and use GPS data to confirm that the user is at home during that time.

[0039] Data Transfer

[0040] The collected data is sent from the device to a server in real time, including calendar information, GPS data, and app usage history.

[0041] Data storage and analysis

[0042] The server stores the received data in a database for each user. It also analyzes the user's behavioral patterns based on the accumulated data. The analysis is performed using an AI model, comparing past data with data from other users.

[0043] Specific examples

[0044] The server analyzes specific behavioral patterns when putting a child to sleep based on data from the past week, and generates effective advice by referencing parenting methods that other users have used successfully.

[0045] Generating Advice

[0046] The server generates parenting advice based on the results of behavioral pattern analysis. The advice is provided in text, video, image, and other formats.

[0047] Specific examples

[0048] The server generates advice including "five effective ways to put a baby to sleep," including the specific method of "gently patting the baby's tummy."

[0049] Providing advice

[0050] The generated child-rearing advice is sent to the user's device at an appropriate time, and the device notifies the user of the received advice and displays it.

[0051] Specific examples

[0052] At 15 minutes (19:45) before bedtime (20:00), the server sends the generated advice to the terminal, which then notifies the user.

[0053] This system allows new fathers to receive specific child-rearing advice in real time that is tailored to their own behavior and environment, reducing the burden of child-rearing and supporting the harmonious development of the family.

[0054] The processing flow will be explained below.

[0055] Step 1:

[0056] Collecting device information

[0057] The user's device collects calendar information, GPS data, and information on the apps they use. It detects childcare-related events (e.g., putting the baby to bed, feeding time) from the calendar information, identifies the user's current location using GPS data, and checks the usage history of childcare-related apps.

[0058] Step 2:

[0059] Sending data

[0060] The device sends the collected data in real time to a server, including calendar information, GPS data, and app usage history.

[0061] Step 3:

[0062] Data storage

[0063] The server stores the received data in a database for each user, and the accumulated data is used to analyze user behavior patterns.

[0064] Step 4:

[0065] Behavioral pattern analysis

[0066] The server analyzes the user's behavioral patterns based on past data and data from other users. It uses an AI model to extract the user's behavioral tendencies and habits and make predictions. It also compares the data with other users to identify parenting methods with a high success rate.

[0067] Step 5:

[0068] Generating Advice

[0069] The server generates parenting advice based on the results of the behavioral pattern analysis. The advice is provided in the form of text, video, images, etc.

[0070] Step 6:

[0071] Sending Advice

[0072] The server transmits the generated child-rearing advice to the user's terminal at an appropriate time.

[0073] Step 7:

[0074] Advice Notification

[0075] The device notifies and displays the received advice to the user, who can then check the specific parenting advice and take action based on it.

[0076] Example 1

[0077] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0078] In recent years, there has been a demand for support systems that can alleviate the anxieties and doubts that new fathers face in child-rearing and provide optimal child-rearing advice. For example, fathers with little experience in child-rearing may find it difficult to determine how to effectively put their children to sleep or what methods are optimal for daily child-rearing. However, existing child-rearing support systems lack the functionality to provide specific advice in real time based on a user's unique behavioral patterns and environmental information. The present invention aims to solve these problems and provide a system that allows new fathers to obtain specific child-rearing advice in real time that is tailored to their own behavior and environment.

[0079] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0080] In this invention, the server includes means for collecting calendar information, location information, and application usage history from the user's device, means for transmitting the collected data to the server in real time, means for storing the data received by the server in a database for each user, means for using a generative AI model to analyze the user's behavioral patterns based on the stored data, means for generating child-rearing advice based on the analysis results, and means for notifying the user's device of the generated child-rearing advice at an appropriate time, thereby making it possible to provide specific and effective child-rearing advice in real time based on the user's unique behavioral patterns and environmental information.

[0081] "User terminal" refers to an electronic device owned by a user, including a smartphone, tablet, or other device that can connect to the Internet.

[0082] "Calendar information" refers to schedule and event information that a user has registered in an electronic calendar.

[0083] "Location information" is data indicating the geographic location of a user obtained using a GPS function or other location measurement means.

[0084] "Application usage history" refers to history information of applications used by a user on a terminal, including specific usage time and activity content.

[0085] "Server" refers to the central processing unit that stores and analyzes collected data and generates and distributes parenting advice.

[0086] A "database" is a system for structuring and managing information stored on a server, including data records for each user.

[0087] A "generative AI model" refers to a program that uses machine learning or artificial intelligence techniques to analyze data and generate parenting advice.

[0088] "Real-time" refers to a process in which data is analyzed and processed almost immediately after it is collected.

[0089] "Behavioral patterns" refer to behavioral tendencies and characteristics analyzed based on a user's past actions and habits.

[0090] "Childcare advice" refers to instructions and suggestions regarding childcare generated based on the user's behavioral patterns and environmental information.

[0091] "Notification" refers to the process of sending messages or alerts from the server to the user's device to provide information to the user.

[0092] MODE FOR CARRYING OUT THE INVENTION

[0093] This system is designed to alleviate the anxieties and doubts that new fathers face in child-rearing and to provide optimal child-rearing advice. A specific embodiment of the system will be described below.

[0094] User behavior data collection

[0095] The user's device collects calendar information, location information, and application usage history. This data is collected using applications installed on smartphones and tablets. For example, the system obtains information such as "Putting kids to bed (20:00)" entered in the user's smartphone calendar. It also uses GPS data to confirm that the user is at home.

[0096] Data Transfer

[0097] The collected data is sent in real time from the device to a server using Wi-Fi or mobile data. The device sends packets containing calendar information, location information, and app usage history.

[0098] Data storage

[0099] The server stores the received data in a database for each individual user. The database is structured and designed to efficiently manage user behavior and environmental information.

[0100] Data analysis

[0101] The server analyzes the user's behavioral patterns based on the stored data. This analysis uses a generative AI model, which compares the user's past data with that of other users to extract the optimal behavioral patterns for the user.

[0102] Specific examples of prompts are as follows:

[0103] "Based on data from the past week, please extract the user's behavioral patterns when putting their child to sleep."

[0104] "Generate effective parenting advice based on other users' successful parenting methods."

[0105] Generating Advice

[0106] The server generates childcare advice based on the results of the behavioral pattern analysis. The advice is provided to the user in text, image, video, or other formats. For example, the server may generate advice including "five effective ways to get a baby to sleep," including the specific method of "gently patting the tummy."

[0107] Providing advice

[0108] The generated parenting advice is sent to the user's device at the appropriate time. The device notifies the user of the received advice and displays it. For example, the server sends the parenting advice to the device 15 minutes (19:45) before bedtime (20:00), and the device notifies the user of the information.

[0109] This system allows new fathers to receive specific child-rearing advice in real time that is tailored to their own behavior and environment, reducing the burden of child-rearing and supporting the harmonious development of the family.

[0110] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0111] Step 1:

[0112] User behavior data collection

[0113] Input: Data related to user behavior and environment (calendar information, location information, application usage history)

[0114] Specific behavior:

[0115] The device accesses the smartphone's calendar app to obtain event information. For example, it detects information that the user has registered in the calendar as "Putting the child to bed (20:00)."

[0116] The device uses a GPS sensor to determine where the user is at that time of day, specifically whether the user is at home.

[0117] The device obtains historical information about the apps the user is using and collects activities related to childcare (e.g., browsing history of childcare apps and websites).

[0118] Output: Collected data (calendar information, location information, application usage history)

[0119] Step 2:

[0120] Data Transfer

[0121] Input: Collected data (calendar information, location information, application usage history)

[0122] Specific behavior:

[0123] The device creates packets containing calendar, GPS, and app history data.

[0124] The device uses Wi-Fi or mobile data to send the created packets to the server.

[0125] Output: Data sent to the server

[0126] Step 3:

[0127] Data storage

[0128] Input: Data sent to the server (calendar information, location information, application usage history)

[0129] Specific behavior:

[0130] The server analyzes the received data and stores it as a data record in a dedicated database table for each user.

[0131] Output: Data stored in the database

[0132] Step 4:

[0133] Data analysis

[0134] Input: Data stored in the database (calendar information, location information, application usage history)

[0135] Specific behavior:

[0136] The server sends an analysis request to the generative AI model using a prompt sentence.

[0137] Example prompt: "Based on data from the past week, please identify patterns in how users put their children to bed."

[0138] The generative AI model returns the analysis results to the server, which then uses this to understand the user's behavioral patterns.

[0139] Output: Analysis results of behavioral patterns

[0140] Step 5:

[0141] Generating Advice

[0142] Input: Analysis results of behavioral patterns

[0143] Specific behavior:

[0144] The server sends prompts to the generative AI model to generate specific parenting advice.

[0145] Example prompt: "What are five effective ways to get your child to sleep?"

[0146] The generative AI model generates advice in the form of text, images, or videos and returns it to the server.

[0147] The server formats the advice it receives and presents it in a form suitable for the user.

[0148] Output: Generated parenting advice (in text, image, and video formats)

[0149] Step 6:

[0150] Providing advice

[0151] Input: Generated parenting advice (text, image, video format)

[0152] Specific behavior:

[0153] The server refers to the user's schedule and sends advice at the optimal time (for example, 15 minutes before putting the child to bed).

[0154] The device receives the advice and notifies the user using the notification function.

[0155] The device displays an appropriate UI screen so that the user can check the advice.

[0156] Output: Parenting advice received and confirmed by the user

[0157] (Application example 1)

[0158] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0159] There is a need to alleviate the anxieties and questions new fathers face when raising children, provide optimal childcare advice in real time, and facilitate the selection of childcare-related products in physical stores. However, conventional systems require users to manually search for information or navigate the store, which creates problems of burden and time-consuming childcare. Furthermore, there is a lack of a way to provide detailed advice in real time tailored to specific situations and locations.

[0160] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0161] In this invention, the server includes means for collecting data from a user's device, means for transmitting the data to the server, means for analyzing the user's behavioral patterns based on the data, means for generating child-rearing advice based on the behavioral pattern analysis, means for notifying the user's device of the child-rearing advice, and means for displaying the child-rearing advice and product information in the store using smart glasses. This makes it easier to obtain information and advice about child-rearing in real time in a physical store, thereby reducing the burden of child-rearing on the user.

[0162] "User" refers to individuals who use the system, especially new fathers.

[0163] "Device" refers to an electronic device used by a user, such as a smartphone or smart glasses.

[0164] "Data" refers to information collected from the device, such as calendar information, GPS data, and app usage history.

[0165] "Server" refers to a computer system for receiving and analyzing data.

[0166] "Behavioral patterns" refer to behavioral trends analyzed based on the user's past data and data from other users.

[0167] "Childcare advice" refers to advice on specific childcare methods and product selection provided based on an analysis of the user's behavioral patterns.

[0168] "Notification" refers to the act of sending childcare advice to the user's device and notifying them at the appropriate time.

[0169] "Smart glasses" refers to a wearable device that is worn by the user and is equipped with a display and camera.

[0170] "In-store" refers to the interior space of a physical store where childcare products are sold.

[0171] "Product information" refers to detailed descriptions of childcare-related products, how to use them, and advice about them.

[0172] This invention is a system that provides optimal childcare advice to new fathers by eliminating their concerns and questions about childcare. The system uses users' devices and a server to collect and analyze data and provide specific childcare advice in real time. It also has the ability to display childcare advice and product information using smart glasses in physical stores.

[0173] Collecting user information

[0174] The user's device collects various data related to the user's behavior and environment. Specifically, it periodically acquires calendar information, GPS data, and information about the apps used. For example, if a user has "Putting the kids to bed (8:00 PM)" registered on their smartphone calendar, the device will detect this information and use GPS data to confirm that the user is at home during that time.

[0175] Data Transfer

[0176] The collected data is sent from the device to a server in real time, including calendar information, GPS data, and app usage history.

[0177] Data storage and analysis

[0178] The server stores the received data in a database for each user. It also analyzes the user's behavioral patterns based on the accumulated data. The analysis is performed by comparing past data with data from other users and using a generative AI model (e.g., GTP-4). The server analyzes the user's specific behavioral patterns when putting their child to sleep based on data from the past week. It also generates effective advice by referring to the parenting methods that other users have used successfully.

[0179] Generating Advice

[0180] The server generates parenting advice based on the results of analyzing behavioral patterns. The advice is provided in text, video, image, and other formats. For example, the server may generate advice including "five effective ways to get a baby to sleep," including the specific method of "gently patting the baby's tummy."

[0181] Providing advice

[0182] The generated parenting advice is sent to the user's device or smart glasses at the appropriate time. The device or smart glasses notifies the user of the received advice and displays it. For example, at 19:45, 15 minutes before bedtime (20:00), the server sends the generated advice to the device, and the device notifies the user.

[0183] Use in physical stores

[0184] This system also uses smart glasses to provide childcare advice and product information within physical stores. As a user walks around a childcare store, the smart glasses detect the user's location and send it to a server. The server generates appropriate product information and childcare advice based on the product location information within the store and the user's data, and displays it on the smart glasses' display.

[0185] Specific examples

[0186] For example, if a user is looking for advice on "diaper changing," the server will display the location of related products (e.g., diapers, baby wipes) and show the features and usage of each product on the smart glasses. Also, if a user wants advice from a generative AI model using a prompt sentence, they can enter a sentence like the following:

[0187] Prompt Sentence Examples

[0188] I'm a new dad and I'm currently struggling with childcare. I have "putting my child to bed (8:00 PM)" scheduled on my calendar, and I'm usually at home during that time. It's hard to find products while raising my child. Could you recommend any products or give me some childcare advice?

[0189] This makes it easier to obtain information and advice about childcare in real time within a physical store, reducing the burden of childcare on users.

[0190] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0191] Step 1:

[0192] The user's device (smartphone or smart glasses) collects data related to the user's behavior and environment. Specifically, it acquires calendar information, GPS data, and information on the apps used. As input, it acquires information such as "Putting the child to bed (20:00)" that the user has registered in their smartphone calendar. As output, this data is stored on the device.

[0193] Step 2:

[0194] The device sends the collected data in real time to the server. The input includes calendar information, GPS data, and app usage history, and the server receives the information as output.

[0195] Step 3:

[0196] The server stores the received data in a database for each user. As input, there are multiple data sent from the terminal, and as output, the database entry corresponding to each user is updated.

[0197] Step 4:

[0198] The server analyzes the user's behavioral patterns based on the stored data. For the analysis, it references past data and data from other users and uses a generative AI model (e.g., GPT-4 (registered trademark)). Data from the past week and other users' data are provided as input, and the user's behavioral patterns are identified as output.

[0199] Step 5:

[0200] The server generates parenting advice based on the results of the behavioral pattern analysis. The generated advice is provided in text, video, or image format. The input includes the results of the behavioral pattern analysis, and the output generates specific parenting advice. For example, the generated advice might be "five effective ways to put your child to sleep."

[0201] Step 6:

[0202] The generated parenting advice is sent to the user's device or smart glasses. The device or smart glasses notifies and displays the received advice to the user. The generated parenting advice is sent from the server as input, and an alert or notification is displayed on the user's device as output.

[0203] Step 7:

[0204] As a user walks around a baby care store, the smart glasses detect the user's location and send it to a server. The input includes GPS data from within the store, and the output conveys the user's real-time location to the server.

[0205] Step 8:

[0206] The server generates appropriate product information and parenting advice based on the product location information in the store and the user data, and displays it on the smart glasses display. The input includes the user's location information and related data, and the output is the product information and parenting advice displayed on the smart glasses.

[0207] The above are the specific processing steps for carrying out the present invention, which make it easier for users to obtain information and advice on childcare in real time, and enable them to smoothly select childcare-related products in physical stores.

[0208] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0209] This invention is a system that provides optimal child-rearing advice by eliminating the anxieties and doubts that new fathers face in child-rearing. This system uses the user's device, a server, and an emotion engine to collect and analyze data and provide specific child-rearing advice in real time.

[0210] Collecting user information

[0211] The device collects various data related to the user's behavior and environment. Specifically, it periodically acquires calendar information, GPS data, and information on the apps used. The device also has an emotion engine that analyzes the user's voice and facial expressions to generate emotion data.

[0212] Specific examples

[0213] If a user has "Putting the child to bed (8:00 PM)" scheduled on their smartphone calendar, the device will detect this information. It will also use GPS data to confirm that the user is at home during that time. Furthermore, the emotion engine will analyze the user's tone of voice and facial expressions to determine whether the user is feeling stressed.

[0214] Data Transfer

[0215] The collected data is sent from the device to a server in real time, including calendar information, GPS data, app usage history, and emotional data.

[0216] Data storage and analysis

[0217] The server stores the received data in a database for each user. It also analyzes the user's behavioral patterns based on the accumulated data. The analysis is performed using an AI model, comparing past data with data from other users. Furthermore, emotional data is used to customize the content of advice.

[0218] Specific examples

[0219] The server analyzes specific behavioral patterns when putting the user to sleep based on data from the past week, and if the user is feeling stressed, it generates advice including relaxation techniques.

[0220] Generating Advice

[0221] The server generates parenting advice based on the results of the behavioral pattern analysis. The advice is provided in text, video, image, and other formats. Based on the emotional data, appropriate advice is added according to the user's emotional state.

[0222] Specific examples

[0223] The server generates advice including "5 effective ways to put a child to sleep," including the specific method of "gently patting the child's stomach." Furthermore, if the user is feeling stressed, it adds a relaxation technique such as "take a deep breath before putting the child to sleep."

[0224] Providing advice

[0225] The generated child-rearing advice is sent to the user's device at an appropriate time, and the device notifies the user of the received advice and displays it.

[0226] Specific examples

[0227] The server sends the generated advice to the device 15 minutes (19:45) before bedtime (20:00), and the device notifies the user. If the user's stress level is high, the device also provides relaxation advice taking that into account.

[0228] This system allows new fathers to receive specific child-rearing advice in real time based on their own behavior, environment, and emotional state, reducing the burden of child-rearing and supporting the harmonious development of the family.

[0229] The processing flow will be explained below.

[0230] Step 1:

[0231] Collecting device information

[0232] The user's device periodically collects calendar information, GPS data, and information about the apps they use. It also uses an emotion engine to analyze the user's voice and facial expressions to generate emotion data. This information is important for understanding the user's behavior and emotional state.

[0233] Specific examples

[0234] The device detects that "Putting the child to bed (20:00)" is registered on the user's calendar. GPS data confirms that the user is at home during that time. The emotion engine analyzes the user's tone of voice and facial expression and determines that the user's stress level is high.

[0235] Step 2:

[0236] Sending data

[0237] The device transmits the collected calendar information, GPS data, history of app usage, and emotion data to the server in real time.

[0238] Step 3:

[0239] Data storage

[0240] The server stores the received data in a database for each user, which is used for further analysis and advice generation.

[0241] Step 4:

[0242] Behavioral pattern analysis

[0243] The server analyzes the user's accumulated data, compares past data with that of other users, extracts the user's behavioral patterns, and makes predictions. Advanced analysis is performed using AI models.

[0244] Specific examples

[0245] The server analyzes calendar data from the past week to determine whether the user tends to put their child to bed at 8 p.m., and also uses emotional data to determine whether the user tends to feel stressed when putting their child to bed.

[0246] Step 5:

[0247] Generating Advice

[0248] The server generates parenting advice tailored to the user based on the analysis of the behavioral patterns and emotional data. The advice is customized according to the user's behavior and emotional state.

[0249] Specific examples

[0250] The server generates advice including "5 effective ways to put a child to sleep," including "gently patting the tummy" as one of the suggestions. Furthermore, considering that the user is feeling stressed, the server adds "taking deep breaths to calm the mind."

[0251] Step 6:

[0252] Sending Advice

[0253] The server transmits the generated child-rearing advice to the user's terminal at an appropriate time.

[0254] Step 7:

[0255] Advice Notification

[0256] The terminal notifies the user of the received advice and displays it, allowing the user to take action based on the advice.

[0257] Specific examples

[0258] The server sends the generated advice to the device 15 minutes before bedtime at 8:00 PM (7:45 PM). The device notifies the user of the advice and displays it. If the user is feeling stressed, the device also provides additional advice on relaxation techniques.

[0259] Through these steps, the system enables new fathers to receive optimal child-rearing advice and effectively resolves their anxieties and questions about child-rearing.

[0260] Example 2

[0261] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0262] To alleviate the anxieties and doubts that new fathers face in child-rearing and provide optimal child-rearing advice, it is necessary to understand the behavior and emotional state of each user and provide specific advice based on that in real time. However, conventional systems have difficulty generating advice that fully reflects each user's individual behavioral patterns and emotional state, resulting in the problem that the advice provided is general and not specific or effective.

[0263] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0264] In this invention, the server includes means for collecting calendar information, location data, and information on software used from the user's device, means for analyzing the collected data to grasp the user's emotional state, means for analyzing the user's behavioral patterns based on the data, means for generating child-rearing advice based on the analysis of the behavioral patterns and emotional state, and means for notifying the user's device of the child-rearing advice, thereby making it possible to provide specific and effective child-rearing advice based on the behavior and emotional state of each individual user in real time.

[0265] A "terminal" is an electronic device used by a user that has functions such as information collection, display, and communication.

[0266] "Calendar information" refers to data about events and schedules that a user has entered into a calendar application on the terminal.

[0267] "Location data" refers to information about a user's geographic location obtained by the user's device, and is collected via a GPS system or the like.

[0268] "Information about software used" is data related to the usage history and usage status of applications used by the user on the terminal.

[0269] "Emotional state" refers to the emotions and psychological state of a user, and is estimated using technologies such as voice analysis and facial expression recognition.

[0270] A "behavioral pattern" is a certain behavioral pattern or habit obtained as a result of analyzing a user's past behavior and behavioral tendencies.

[0271] "Childcare advice" is information such as specific instructions, suggestions, and advice regarding childcare, and is generated based on the user's behavioral patterns and emotional state.

[0272] A "server" is a computer system that communicates with terminals via a network, stores data, analyzes, processes data, and provides information.

[0273] "Means of collection" refers to the functions and processes for obtaining various data from the device (calendar information, location data, information on software used).

[0274] "Means of analysis" refers to the functions and processes for analyzing and processing the user's behavioral patterns and emotional state based on the collected data.

[0275] The "notification means" refers to a function or process for sending the generated child-rearing advice to the user's terminal and notifying the user.

[0276] This invention is a system that provides optimal child-rearing advice by eliminating the anxieties and doubts that new fathers face in child-rearing. This system utilizes the user's device, a server, and an emotion engine to collect and analyze data and provide specific child-rearing advice in real time.

[0277] Collecting user information

[0278] The user's device is equipped with hardware and software for collecting various data, including a calendar application, a GPS module, and software for monitoring the usage of various applications. It also includes an emotion engine for analyzing the user's voice and facial expressions.

[0279] As a concrete example of the "Mode for Carrying Out the Invention," consider a case where a user has entered "Putting the child to bed (20:00)" in their smartphone calendar. In this system, the device detects this information and simultaneously confirms via GPS data that the user is at home at that time. Furthermore, the emotion engine analyzes the user's tone of voice and facial expression to determine their stress level.

[0280] Data Transfer and Storage

[0281] The collected data is sent in real time from the user's device to a server, including calendar information, GPS data, app usage history, and emotional data.

[0282] The server stores the received data in a database for each user. The stored data is managed in a format linked to the user ID and is later used to analyze behavioral patterns.

[0283] Analyzing data and generating advice

[0284] The server uses an AI model based on the accumulated data to analyze the user's behavioral patterns. This analysis compares past data with other users' data to obtain highly accurate results. It also uses emotional data to understand the user's emotional state and customize the advice provided.

[0285] For example, the server analyzes specific behavioral patterns when putting a child to bed based on data from the past week, and if the user is experiencing high stress levels, generates advice including relaxation techniques.

[0286] The server generates parenting advice based on the analysis results. This advice is provided in text, image, video, and other formats. For example, advice can be generated that includes "five effective ways to put your child to sleep," including the specific method of "gently patting the child's tummy." Furthermore, if the user is feeling stressed, the server can add relaxation tips, such as "take a deep breath before putting the child to sleep."

[0287] Providing advice

[0288] The generated childcare advice is sent to the user's device at the appropriate time. The device notifies the user of the received advice and displays it. As a specific example, the server sends the generated advice to the device 15 minutes (19:45) before bedtime (20:00), and the device notifies the user. At this time, if the user's emotional data indicates a high stress level, the device will also notify the user of relaxation methods that take this into consideration.

[0289] This allows new fathers to receive specific child-rearing advice in real time that is tailored to their own behavior, environment, and emotional state, reducing the burden of child-rearing and supporting the harmonious development of their families.

[0290] (Example of a prompt)

[0291] "How do I help my baby relax while I'm getting him to sleep?"

[0292] "What are some easy ways to relax when you're stressed?"

[0293] "Please tell me the specific steps to make getting your child to sleep easier."

[0294] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0295] Step 1:

[0296] Collecting user information

[0297] The device collects calendar information, location data, and information about the software being used. Input data includes calendar information registered by the user on the device, location data obtained from the GPS module, and information about the applications being used. The device periodically obtains this data and temporarily stores the collected information. Specifically, it obtains schedule information from the calendar app, checks the user's current location from GPS data, and records the history of the applications being used.

[0298] Step 2:

[0299] Emotional state analysis

[0300] The device inputs the collected voice and facial expression data into an emotion engine, which outputs it as emotional data. The emotion engine uses voice analysis and facial recognition technology to analyze the user's emotional state. It receives voice data and facial expression images as input, and generates data representing stress levels and emotional states as output. Specifically, it analyzes voice recorded using a microphone and facial expressions captured with a camera.

[0301] Step 3:

[0302] Data Transfer

[0303] The device sends the collected calendar information, location data, information on the software used, and emotion data to the server. The input data is information stored in the device, and the output data is data packets sent to the server. Specifically, the device sends all collected data to the server at regular intervals.

[0304] Step 4:

[0305] Data storage

[0306] The server stores the received data in a database. Input data includes calendar information, location data, software used, and emotion data sent from the device, and the output is a database entry. Specifically, the server analyzes the received data, associates it with the user ID, and records it in the database.

[0307] Step 5:

[0308] Analysis of behavioral patterns and emotional states

[0309] The server analyzes the user's behavioral patterns and emotional state based on the received data. The input data includes past data and data from other users, and the output is the analysis results. Specifically, the server inputs the data into an AI model, which then analyzes the user's behavioral patterns and emotional state.

[0310] Step 6:

[0311] Generating Advice

[0312] The server generates parenting advice based on the results of analyzing behavioral patterns and emotional data. The input data are the results of behavioral pattern analysis and emotional state analysis, and the output is parenting advice. In concrete terms, the server uses the generative AI model to create parenting advice in text, image, and video format that is optimal for the user's condition.

[0313] Step 7:

[0314] Providing advice

[0315] The server sends the generated parenting advice to the user's device, which then notifies and displays it to the user. The generated parenting advice is input data, and the advice is displayed on the user's device as output. Specifically, the server sends the generated advice to the device at the appropriate time, and the device notifies the user via push notification, etc.

[0316] (Application example 2)

[0317] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0318] Today's new fathers often face many anxieties and questions about child-rearing. In particular, they lack advice tailored to their specific child-rearing situations and support that takes into account the father's own emotional state. This can increase stress and result in a decline in the quality of child-rearing. Because conventional systems do not provide customized advice based on emotional states and behavioral patterns, an effective solution to this problem is needed.

[0319] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting data from the user's terminal, means for analyzing the user's behavioral patterns based on the data, and means for customizing advice based on emotional data. This makes it possible to provide child-rearing advice that is suited to the user's specific behavioral patterns and emotional state.

[0320] "User's terminal" is a general term for a communication-enabled device used by a user, and mainly refers to a smartphone, smart glasses, a head-mounted display, or a robot.

[0321] "Data" refers to all information related to the user's behavior and environment, including calendar information, GPS data, information about the apps used, and emotional data generated from voice and facial expressions.

[0322] "Server" means a computer system on a network that receives and stores data, analyzes it, generates advice, and sends it to a user's device.

[0323] "Behavioral patterns" refer to specific behavioral patterns or tendencies derived from a user's past and present behavior.

[0324] "Emotion data" refers to information about the user's emotional state obtained by analyzing the user's voice and facial expressions.

[0325] "Parenting advice" refers to specific and practical guidance and suggestions regarding child-rearing that are generated based on the user's behavioral patterns and emotional state.

[0326] "Customization" refers to the process of tailoring advice content to a user's individual behavioral patterns and emotional state.

[0327] "Notification" refers to the act of sending childcare advice to the user's device in real time to inform the user.

[0328] This invention is a system that resolves the anxieties and doubts that new fathers face in child-rearing and provides optimal child-rearing advice in real time. The system consists of a user terminal, a server, and an emotion engine.

[0329] System configuration

[0330] User's device

[0331] The user's device is a communication-enabled device such as a smartphone, smart glasses, a head-mounted display, or a robot. The device collects the following data:

[0332] Calendar information: Get scheduled childcare activities and more.

[0333] GPS data: Obtaining the user's location.

[0334] App usage information: Obtain a history of apps used by the user.

[0335] Emotional data: The user's emotional state is obtained through analysis of voice and facial expressions.

[0336] Data collection and analysis

[0337] 1. Data Collection

[0338] The device periodically collects various data related to the user's behavior and environment. The emotion engine analyzes the user's voice and facial expressions to generate emotion data.

[0339] 2. Data Transfer

[0340] The collected data is sent to a server in real time.

[0341] Processing on the server

[0342] 1. Data storage and analysis

[0343] The server stores the received data in a database for each user. The stored data is used to analyze the user's behavioral patterns. The analysis is performed by comparing the data with past data and data from other users. The content of advice is also customized based on emotional data.

[0344] Hardware and software used

[0345] Hardware: Servers, databases, smartphones

[0346] Software: Python, API, TENSORFLOW (registered trademark), Django (or Flask), sentiment analysis engine

[0347] Generating and Serving Advice

[0348] 1. Advice Generation

[0349] The server generates parenting advice based on the analysis results. The advice is provided in text, video, image, and other formats. Based on the emotional data, the server customizes the advice to suit the user's emotional state.

[0350] 2. Advice Notice

[0351] The generated child-rearing advice is notified to the user's terminal in real time shortly before the time of the user's specific activity.

[0352] Specific examples

[0353] For example, if a user plans to put their child to bed at 8:00 PM, the device will collect that information and notify them of advice generated by the server at 7:45 PM. If the user's stress level is determined to be high, they will also be notified of relaxation techniques.

[0354] Prompt Sentence Examples

[0355] The user is in the following emotional state: Stress

[0356] Recent patterns of behavior include:

[0357] Calendar: Bedtime (20:00)

[0358] GPS Location: Home

[0359] App usage history: Parenting apps, relaxation apps

[0360] Generate specific parenting advice, including "5 effective ways to get your baby to sleep," to address any concerns or questions users may have. Also, provide relaxation advice if users are feeling stressed.

[0361] This invention allows new fathers to receive specific child-rearing advice in real time that is tailored to their own behavior, environment, and emotional state, reducing the burden of child-rearing and supporting the harmonious development of the family.

[0362] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0363] Step 1:

[0364] The device collects data related to the user's behavior and environment. Specifically, it acquires calendar information, GPS data, information on the apps used, and emotional data generated from voice and facial expressions. The input data is the user's calendar information, GPS location information, app usage history, voice data, and video data, and the output data is a set of collected data including this information.

[0365] Step 2:

[0366] The terminal transmits the collected data to the server in real time. The input data is the data collected in step 1, and the output data is the data transmitted to the server. The specific transmission operation uses a communication protocol such as an HTTP request or WebSocket.

[0367] Step 3:

[0368] The server stores the data it receives in a database. The input data is the data sent from the terminal, and the output data is the stored database entry. Specifically, it executes an INSERT statement against a database (e.g., MySQL (registered trademark) or PostgreSQL).

[0369] Step 4:

[0370] The server analyzes the user's behavioral patterns based on the stored data. The input data is past data stored in the database and data from other users, and the output data is the analysis results of the behavioral patterns. Specifically, the data is analyzed using a machine learning model (e.g., TensorFlow or PyTorch).

[0371] Step 5:

[0372] The server generates advice based on the user's emotional data. The input data are the analysis results of behavioral patterns and emotional data, and the output data is the generated parenting advice. Specifically, the system uses an emotion analysis engine to generate prompt sentences, which are then input into the AI ​​model to obtain advice.

[0373] Step 6:

[0374] The server notifies the user's device of the generated parenting advice. The input data is the generated advice, and the output data is the notification sent to the device. Specifically, the advice is sent to the device using a push notification service (e.g., Firebase Cloud Messaging).

[0375] Users can receive real-time advice based on specific activity times, which can improve the quality of their child-rearing. This series of processing steps realizes a system that effectively solves many of the challenges new fathers face in child-rearing.

[0376] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0377] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0378] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0379] [Second embodiment]

[0380] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0381] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0382] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0383] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0384] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0385] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0386] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0387] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0388] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0389] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0390] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0391] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0392] This invention is a system that provides optimal child-rearing advice by eliminating the anxieties and doubts that new fathers face in child-rearing. This system uses the user's device and a server to collect and analyze data and provide specific child-rearing advice in real time.

[0393] Collecting user information

[0394] The device collects various data related to the user's behavior and environment, specifically, calendar information, GPS data, and information about the apps used, on a regular basis.

[0395] Specific examples

[0396] If a user has "Putting the child to bed (20:00)" scheduled on their smartphone calendar, the device will detect this information and use GPS data to confirm that the user is at home during that time.

[0397] Data Transfer

[0398] The collected data is sent from the device to a server in real time, including calendar information, GPS data, and app usage history.

[0399] Data storage and analysis

[0400] The server stores the received data in a database for each user. It also analyzes the user's behavioral patterns based on the accumulated data. The analysis is performed using an AI model, comparing past data with data from other users.

[0401] Specific examples

[0402] The server analyzes specific behavioral patterns when putting a child to sleep based on data from the past week, and generates effective advice by referencing parenting methods that other users have used successfully.

[0403] Generating Advice

[0404] The server generates parenting advice based on the results of behavioral pattern analysis. The advice is provided in text, video, image, and other formats.

[0405] Specific examples

[0406] The server generates advice including "five effective ways to put a baby to sleep," including the specific method of "gently patting the baby's tummy."

[0407] Providing advice

[0408] The generated child-rearing advice is sent to the user's device at an appropriate time, and the device notifies the user of the received advice and displays it.

[0409] Specific examples

[0410] At 15 minutes (19:45) before bedtime (20:00), the server sends the generated advice to the terminal, which then notifies the user.

[0411] This system allows new fathers to receive specific child-rearing advice in real time that is tailored to their own behavior and environment, reducing the burden of child-rearing and supporting the harmonious development of the family.

[0412] The processing flow will be explained below.

[0413] Step 1:

[0414] Collecting device information

[0415] The user's device collects calendar information, GPS data, and information on the apps they use. It detects childcare-related events (e.g., putting the baby to bed, feeding time) from the calendar information, identifies the user's current location using GPS data, and checks the usage history of childcare-related apps.

[0416] Step 2:

[0417] Sending data

[0418] The device sends the collected data in real time to a server, including calendar information, GPS data, and app usage history.

[0419] Step 3:

[0420] Data storage

[0421] The server stores the received data in a database for each user, and the accumulated data is used to analyze user behavior patterns.

[0422] Step 4:

[0423] Behavioral pattern analysis

[0424] The server analyzes the user's behavioral patterns based on past data and data from other users. It uses an AI model to extract the user's behavioral tendencies and habits and make predictions. It also compares the data with other users to identify parenting methods with a high success rate.

[0425] Step 5:

[0426] Generating Advice

[0427] The server generates parenting advice based on the results of the behavioral pattern analysis. The advice is provided in the form of text, video, images, etc.

[0428] Step 6:

[0429] Sending Advice

[0430] The server transmits the generated child-rearing advice to the user's terminal at an appropriate time.

[0431] Step 7:

[0432] Advice Notification

[0433] The device notifies and displays the received advice to the user, who can then check the specific parenting advice and take action based on it.

[0434] Example 1

[0435] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0436] In recent years, there has been a demand for support systems that can alleviate the anxieties and doubts that new fathers face in child-rearing and provide optimal child-rearing advice. For example, fathers with little experience in child-rearing may find it difficult to determine how to effectively put their children to sleep or what methods are optimal for daily child-rearing. However, existing child-rearing support systems lack the functionality to provide specific advice in real time based on a user's unique behavioral patterns and environmental information. The present invention aims to solve these problems and provide a system that allows new fathers to obtain specific child-rearing advice in real time that is tailored to their own behavior and environment.

[0437] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0438] In this invention, the server includes means for collecting calendar information, location information, and application usage history from the user's device, means for transmitting the collected data to the server in real time, means for storing the data received by the server in a database for each user, means for using a generative AI model to analyze the user's behavioral patterns based on the stored data, means for generating child-rearing advice based on the analysis results, and means for notifying the user's device of the generated child-rearing advice at an appropriate time, thereby making it possible to provide specific and effective child-rearing advice in real time based on the user's unique behavioral patterns and environmental information.

[0439] "User terminal" refers to an electronic device owned by a user, including a smartphone, tablet, or other device that can connect to the Internet.

[0440] "Calendar information" refers to schedule and event information that a user has registered in an electronic calendar.

[0441] "Location information" is data indicating the geographic location of a user obtained using a GPS function or other location measurement means.

[0442] "Application usage history" refers to history information of applications used by a user on a terminal, including specific usage time and activity content.

[0443] "Server" refers to the central processing unit that stores and analyzes collected data and generates and distributes parenting advice.

[0444] A "database" is a system for structuring and managing information stored on a server, including data records for each user.

[0445] A "generative AI model" refers to a program that uses machine learning or artificial intelligence techniques to analyze data and generate parenting advice.

[0446] "Real-time" refers to a process in which data is analyzed and processed almost immediately after it is collected.

[0447] "Behavioral patterns" refer to behavioral tendencies and characteristics analyzed based on a user's past actions and habits.

[0448] "Childcare advice" refers to instructions and suggestions regarding childcare generated based on the user's behavioral patterns and environmental information.

[0449] "Notification" refers to the process of sending messages or alerts from the server to the user's device to provide information to the user.

[0450] MODE FOR CARRYING OUT THE INVENTION

[0451] This system is designed to alleviate the anxieties and doubts that new fathers face in child-rearing and to provide optimal child-rearing advice. A specific embodiment of the system will be described below.

[0452] User behavior data collection

[0453] The user's device collects calendar information, location information, and application usage history. This data is collected using applications installed on smartphones and tablets. For example, the system obtains information such as "Putting kids to bed (20:00)" entered in the user's smartphone calendar. It also uses GPS data to confirm that the user is at home.

[0454] Data Transfer

[0455] The collected data is sent in real time from the device to a server using Wi-Fi or mobile data. The device sends packets containing calendar information, location information, and app usage history.

[0456] Data storage

[0457] The server stores the received data in a database for each individual user. The database is structured and designed to efficiently manage user behavior and environmental information.

[0458] Data analysis

[0459] The server analyzes the user's behavioral patterns based on the stored data. This analysis uses a generative AI model, which compares the user's past data with that of other users to extract the optimal behavioral patterns for the user.

[0460] Specific examples of prompts are as follows:

[0461] "Based on data from the past week, please extract the user's behavioral patterns when putting their child to sleep."

[0462] "Generate effective parenting advice based on other users' successful parenting methods."

[0463] Generating Advice

[0464] The server generates childcare advice based on the results of the behavioral pattern analysis. The advice is provided to the user in text, image, video, or other formats. For example, the server may generate advice including "five effective ways to get a baby to sleep," including the specific method of "gently patting the tummy."

[0465] Providing advice

[0466] The generated parenting advice is sent to the user's device at the appropriate time. The device notifies the user of the received advice and displays it. For example, the server sends the parenting advice to the device 15 minutes (19:45) before bedtime (20:00), and the device notifies the user of the information.

[0467] This system allows new fathers to receive specific child-rearing advice in real time that is tailored to their own behavior and environment, reducing the burden of child-rearing and supporting the harmonious development of the family.

[0468] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0469] Step 1:

[0470] User behavior data collection

[0471] Input: Data related to user behavior and environment (calendar information, location information, application usage history)

[0472] Specific behavior:

[0473] The device accesses the smartphone's calendar app to obtain event information. For example, it detects information that the user has registered in the calendar as "Putting the child to bed (20:00)."

[0474] The device uses a GPS sensor to determine where the user is at that time of day, specifically whether the user is at home.

[0475] The device obtains historical information about the apps the user is using and collects activities related to childcare (e.g., browsing history of childcare apps and websites).

[0476] Output: Collected data (calendar information, location information, application usage history)

[0477] Step 2:

[0478] Data Transfer

[0479] Input: Collected data (calendar information, location information, application usage history)

[0480] Specific behavior:

[0481] The device creates packets containing calendar, GPS, and app history data.

[0482] The device uses Wi-Fi or mobile data to send the created packets to the server.

[0483] Output: Data sent to the server

[0484] Step 3:

[0485] Data storage

[0486] Input: Data sent to the server (calendar information, location information, application usage history)

[0487] Specific behavior:

[0488] The server analyzes the received data and stores it as a data record in a dedicated database table for each user.

[0489] Output: Data stored in the database

[0490] Step 4:

[0491] Data analysis

[0492] Input: Data stored in the database (calendar information, location information, application usage history)

[0493] Specific behavior:

[0494] The server sends an analysis request to the generative AI model using a prompt sentence.

[0495] Example prompt: "Based on data from the past week, please identify patterns in how users put their children to bed."

[0496] The generative AI model returns the analysis results to the server, which then uses this to understand the user's behavioral patterns.

[0497] Output: Analysis results of behavioral patterns

[0498] Step 5:

[0499] Generating Advice

[0500] Input: Analysis results of behavioral patterns

[0501] Specific behavior:

[0502] The server sends prompts to the generative AI model to generate specific parenting advice.

[0503] Example prompt: "What are five effective ways to get your child to sleep?"

[0504] The generative AI model generates advice in the form of text, images, or videos and returns it to the server.

[0505] The server formats the advice it receives and presents it in a form suitable for the user.

[0506] Output: Generated parenting advice (in text, image, and video formats)

[0507] Step 6:

[0508] Providing advice

[0509] Input: Generated parenting advice (text, image, video format)

[0510] Specific behavior:

[0511] The server refers to the user's schedule and sends advice at the optimal time (for example, 15 minutes before putting the child to bed).

[0512] The device receives the advice and notifies the user using the notification function.

[0513] The device displays an appropriate UI screen so that the user can check the advice.

[0514] Output: Parenting advice received and confirmed by the user

[0515] (Application example 1)

[0516] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0517] There is a need to alleviate the anxieties and questions new fathers face when raising children, provide optimal childcare advice in real time, and facilitate the selection of childcare-related products in physical stores. However, conventional systems require users to manually search for information or navigate the store, which creates problems of burden and time-consuming childcare. Furthermore, there is a lack of a way to provide detailed advice in real time tailored to specific situations and locations.

[0518] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0519] In this invention, the server includes means for collecting data from a user's device, means for transmitting the data to the server, means for analyzing the user's behavioral patterns based on the data, means for generating child-rearing advice based on the behavioral pattern analysis, means for notifying the user's device of the child-rearing advice, and means for displaying the child-rearing advice and product information in the store using smart glasses. This makes it easier to obtain information and advice about child-rearing in real time in a physical store, thereby reducing the burden of child-rearing on the user.

[0520] "User" refers to individuals who use the system, especially new fathers.

[0521] "Device" refers to an electronic device used by a user, such as a smartphone or smart glasses.

[0522] "Data" refers to information collected from the device, such as calendar information, GPS data, and app usage history.

[0523] "Server" refers to a computer system for receiving and analyzing data.

[0524] "Behavioral patterns" refer to behavioral trends analyzed based on the user's past data and data from other users.

[0525] "Childcare advice" refers to advice on specific childcare methods and product selection provided based on an analysis of the user's behavioral patterns.

[0526] "Notification" refers to the act of sending childcare advice to the user's device and notifying them at the appropriate time.

[0527] "Smart glasses" refers to a wearable device that is worn by the user and is equipped with a display and camera.

[0528] "In-store" refers to the interior space of a physical store where childcare products are sold.

[0529] "Product information" refers to detailed descriptions of childcare-related products, how to use them, and advice about them.

[0530] This invention is a system that provides optimal childcare advice to new fathers by eliminating their concerns and questions about childcare. The system uses users' devices and a server to collect and analyze data and provide specific childcare advice in real time. It also has the ability to display childcare advice and product information using smart glasses in physical stores.

[0531] Collecting user information

[0532] The user's device collects various data related to the user's behavior and environment. Specifically, it periodically acquires calendar information, GPS data, and information about the apps used. For example, if a user has "Putting the kids to bed (8:00 PM)" registered on their smartphone calendar, the device will detect this information and use GPS data to confirm that the user is at home during that time.

[0533] Data Transfer

[0534] The collected data is sent from the device to a server in real time, including calendar information, GPS data, and app usage history.

[0535] Data storage and analysis

[0536] The server stores the received data in a database for each user. It also analyzes the user's behavioral patterns based on the accumulated data. The analysis is performed by comparing past data with data from other users and using a generative AI model (e.g., GTP-4). The server analyzes the user's specific behavioral patterns when putting their child to sleep based on data from the past week. It also generates effective advice by referring to the parenting methods that other users have used successfully.

[0537] Generating Advice

[0538] The server generates parenting advice based on the results of analyzing behavioral patterns. The advice is provided in text, video, image, and other formats. For example, the server may generate advice including "five effective ways to get a baby to sleep," including the specific method of "gently patting the baby's tummy."

[0539] Providing advice

[0540] The generated parenting advice is sent to the user's device or smart glasses at the appropriate time. The device or smart glasses notifies the user of the received advice and displays it. For example, at 19:45, 15 minutes before bedtime (20:00), the server sends the generated advice to the device, and the device notifies the user.

[0541] Use in physical stores

[0542] This system also uses smart glasses to provide childcare advice and product information within physical stores. As a user walks around a childcare store, the smart glasses detect the user's location and send it to a server. The server generates appropriate product information and childcare advice based on the product location information within the store and the user's data, and displays it on the smart glasses' display.

[0543] Specific examples

[0544] For example, if a user is looking for advice on "diaper changing," the server will display the location of related products (e.g., diapers, baby wipes) and show the features and usage of each product on the smart glasses. Also, if a user wants advice from a generative AI model using a prompt sentence, they can enter a sentence like the following:

[0545] Prompt Sentence Examples

[0546] I'm a new dad and I'm currently struggling with childcare. I have "putting my child to bed (8:00 PM)" scheduled on my calendar, and I'm usually at home during that time. It's hard to find products while raising my child. Could you recommend any products or give me some childcare advice?

[0547] This makes it easier to obtain information and advice about childcare in real time within a physical store, reducing the burden of childcare on users.

[0548] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0549] Step 1:

[0550] The user's device (smartphone or smart glasses) collects data related to the user's behavior and environment. Specifically, it acquires calendar information, GPS data, and information on the apps used. As input, it acquires information such as "Putting the child to bed (20:00)" that the user has registered in their smartphone calendar. As output, this data is stored on the device.

[0551] Step 2:

[0552] The device sends the collected data in real time to the server. The input includes calendar information, GPS data, and app usage history, and the server receives the information as output.

[0553] Step 3:

[0554] The server stores the received data in a database for each user. As input, there are multiple data sent from the terminal, and as output, the database entry corresponding to each user is updated.

[0555] Step 4:

[0556] The server analyzes the user's behavioral patterns based on the stored data. For the analysis, it references past data and data from other users and uses a generative AI model (e.g., GPT-4). Data from the past week and other users are provided as input, and the user's behavioral patterns are identified as output.

[0557] Step 5:

[0558] The server generates parenting advice based on the results of the behavioral pattern analysis. The generated advice is provided in text, video, or image format. The input includes the results of the behavioral pattern analysis, and the output generates specific parenting advice. For example, the generated advice might be "five effective ways to put your child to sleep."

[0559] Step 6:

[0560] The generated parenting advice is sent to the user's device or smart glasses. The device or smart glasses notifies and displays the received advice to the user. The generated parenting advice is sent from the server as input, and an alert or notification is displayed on the user's device as output.

[0561] Step 7:

[0562] As a user walks around a baby care store, the smart glasses detect the user's location and send it to a server. The input includes GPS data from within the store, and the output conveys the user's real-time location to the server.

[0563] Step 8:

[0564] The server generates appropriate product information and parenting advice based on the product location information in the store and the user data, and displays it on the smart glasses display. The input includes the user's location information and related data, and the output is the product information and parenting advice displayed on the smart glasses.

[0565] The above are the specific processing steps for carrying out the present invention, which make it easier for users to obtain information and advice on childcare in real time, and enable them to smoothly select childcare-related products in physical stores.

[0566] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0567] This invention is a system that provides optimal child-rearing advice by eliminating the anxieties and doubts that new fathers face in child-rearing. This system uses the user's device, a server, and an emotion engine to collect and analyze data and provide specific child-rearing advice in real time.

[0568] Collecting user information

[0569] The device collects various data related to the user's behavior and environment. Specifically, it periodically acquires calendar information, GPS data, and information on the apps used. The device also has an emotion engine that analyzes the user's voice and facial expressions to generate emotion data.

[0570] Specific examples

[0571] If a user has "Putting the child to bed (8:00 PM)" scheduled on their smartphone calendar, the device will detect this information. It will also use GPS data to confirm that the user is at home during that time. Furthermore, the emotion engine will analyze the user's tone of voice and facial expressions to determine whether the user is feeling stressed.

[0572] Data Transfer

[0573] The collected data is sent from the device to a server in real time, including calendar information, GPS data, app usage history, and emotional data.

[0574] Data storage and analysis

[0575] The server stores the received data in a database for each user. It also analyzes the user's behavioral patterns based on the accumulated data. The analysis is performed using an AI model, comparing past data with data from other users. Furthermore, emotional data is used to customize the content of advice.

[0576] Specific examples

[0577] The server analyzes specific behavioral patterns when putting the user to sleep based on data from the past week, and if the user is feeling stressed, it generates advice including relaxation techniques.

[0578] Generating Advice

[0579] The server generates parenting advice based on the results of the behavioral pattern analysis. The advice is provided in text, video, image, and other formats. Based on the emotional data, appropriate advice is added according to the user's emotional state.

[0580] Specific examples

[0581] The server generates advice including "5 effective ways to put a child to sleep," including the specific method of "gently patting the child's stomach." Furthermore, if the user is feeling stressed, it adds a relaxation technique such as "take a deep breath before putting the child to sleep."

[0582] Providing advice

[0583] The generated child-rearing advice is sent to the user's device at an appropriate time, and the device notifies the user of the received advice and displays it.

[0584] Specific examples

[0585] The server sends the generated advice to the device 15 minutes (19:45) before bedtime (20:00), and the device notifies the user. If the user's stress level is high, the device also provides relaxation advice taking that into account.

[0586] This system allows new fathers to receive specific child-rearing advice in real time based on their own behavior, environment, and emotional state, reducing the burden of child-rearing and supporting the harmonious development of the family.

[0587] The processing flow will be explained below.

[0588] Step 1:

[0589] Collecting device information

[0590] The user's device periodically collects calendar information, GPS data, and information about the apps they use. It also uses an emotion engine to analyze the user's voice and facial expressions to generate emotion data. This information is important for understanding the user's behavior and emotional state.

[0591] Specific examples

[0592] The device detects that "Putting the child to bed (20:00)" is registered on the user's calendar. GPS data confirms that the user is at home during that time. The emotion engine analyzes the user's tone of voice and facial expression and determines that the user's stress level is high.

[0593] Step 2:

[0594] Sending data

[0595] The device transmits the collected calendar information, GPS data, history of app usage, and emotion data to the server in real time.

[0596] Step 3:

[0597] Data storage

[0598] The server stores the received data in a database for each user, which is used for further analysis and advice generation.

[0599] Step 4:

[0600] Behavioral pattern analysis

[0601] The server analyzes the user's accumulated data, compares past data with that of other users, extracts the user's behavioral patterns, and makes predictions. Advanced analysis is performed using AI models.

[0602] Specific examples

[0603] The server analyzes calendar data from the past week to determine whether the user tends to put their child to bed at 8 p.m., and also uses emotional data to determine whether the user tends to feel stressed when putting their child to bed.

[0604] Step 5:

[0605] Generating Advice

[0606] The server generates parenting advice tailored to the user based on the analysis of the behavioral patterns and emotional data. The advice is customized according to the user's behavior and emotional state.

[0607] Specific examples

[0608] The server generates advice including "5 effective ways to put a child to sleep," including "gently patting the tummy" as one of the suggestions. Furthermore, considering that the user is feeling stressed, the server adds "taking deep breaths to calm the mind."

[0609] Step 6:

[0610] Sending Advice

[0611] The server transmits the generated child-rearing advice to the user's terminal at an appropriate time.

[0612] Step 7:

[0613] Advice Notification

[0614] The terminal notifies the user of the received advice and displays it, allowing the user to take action based on the advice.

[0615] Specific examples

[0616] The server sends the generated advice to the device 15 minutes before bedtime at 8:00 PM (7:45 PM). The device notifies the user of the advice and displays it. If the user is feeling stressed, the device also provides additional advice on relaxation techniques.

[0617] Through these steps, the system enables new fathers to receive optimal child-rearing advice and effectively resolves their anxieties and questions about child-rearing.

[0618] Example 2

[0619] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0620] To alleviate the anxieties and doubts that new fathers face in child-rearing and provide optimal child-rearing advice, it is necessary to understand the behavior and emotional state of each user and provide specific advice based on that in real time. However, conventional systems have difficulty generating advice that fully reflects each user's individual behavioral patterns and emotional state, resulting in the problem that the advice provided is general and not specific or effective.

[0621] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0622] In this invention, the server includes means for collecting calendar information, location data, and information on software used from the user's device, means for analyzing the collected data to grasp the user's emotional state, means for analyzing the user's behavioral patterns based on the data, means for generating child-rearing advice based on the analysis of the behavioral patterns and emotional state, and means for notifying the user's device of the child-rearing advice, thereby making it possible to provide specific and effective child-rearing advice based on the behavior and emotional state of each individual user in real time.

[0623] A "terminal" is an electronic device used by a user that has functions such as information collection, display, and communication.

[0624] "Calendar information" refers to data about events and schedules that a user has entered into a calendar application on the terminal.

[0625] "Location data" refers to information about a user's geographic location obtained by the user's device, and is collected via a GPS system or the like.

[0626] "Information about software used" is data related to the usage history and usage status of applications used by the user on the terminal.

[0627] "Emotional state" refers to the emotions and psychological state of a user, and is estimated using technologies such as voice analysis and facial expression recognition.

[0628] A "behavioral pattern" is a certain behavioral pattern or habit obtained as a result of analyzing a user's past behavior and behavioral tendencies.

[0629] "Childcare advice" is information such as specific instructions, suggestions, and advice regarding childcare, and is generated based on the user's behavioral patterns and emotional state.

[0630] A "server" is a computer system that communicates with terminals via a network, stores data, analyzes, processes data, and provides information.

[0631] "Means of collection" refers to the functions and processes for obtaining various data from the device (calendar information, location data, information on software used).

[0632] "Means of analysis" refers to the functions and processes for analyzing and processing the user's behavioral patterns and emotional state based on the collected data.

[0633] The "notification means" refers to a function or process for sending the generated child-rearing advice to the user's terminal and notifying the user.

[0634] This invention is a system that provides optimal child-rearing advice by eliminating the anxieties and doubts that new fathers face in child-rearing. This system utilizes the user's device, a server, and an emotion engine to collect and analyze data and provide specific child-rearing advice in real time.

[0635] Collecting user information

[0636] The user's device is equipped with hardware and software for collecting various data, including a calendar application, a GPS module, and software for monitoring the usage of various applications. It also includes an emotion engine for analyzing the user's voice and facial expressions.

[0637] As a concrete example of the "Mode for Carrying Out the Invention," consider a case where a user has entered "Putting the child to bed (20:00)" in their smartphone calendar. In this system, the device detects this information and simultaneously confirms via GPS data that the user is at home at that time. Furthermore, the emotion engine analyzes the user's tone of voice and facial expression to determine their stress level.

[0638] Data Transfer and Storage

[0639] The collected data is sent in real time from the user's device to a server, including calendar information, GPS data, app usage history, and emotional data.

[0640] The server stores the received data in a database for each user. The stored data is managed in a format linked to the user ID and is later used to analyze behavioral patterns.

[0641] Analyzing data and generating advice

[0642] The server uses an AI model based on the accumulated data to analyze the user's behavioral patterns. This analysis compares past data with other users' data to obtain highly accurate results. It also uses emotional data to understand the user's emotional state and customize the advice provided.

[0643] For example, the server analyzes specific behavioral patterns when putting a child to bed based on data from the past week, and if the user is experiencing high stress levels, generates advice including relaxation techniques.

[0644] The server generates parenting advice based on the analysis results. This advice is provided in text, image, video, and other formats. For example, advice can be generated that includes "five effective ways to put your child to sleep," including the specific method of "gently patting the child's tummy." Furthermore, if the user is feeling stressed, the server can add relaxation tips, such as "take a deep breath before putting the child to sleep."

[0645] Providing advice

[0646] The generated childcare advice is sent to the user's device at the appropriate time. The device notifies the user of the received advice and displays it. As a specific example, the server sends the generated advice to the device 15 minutes (19:45) before bedtime (20:00), and the device notifies the user. At this time, if the user's emotional data indicates a high stress level, the device will also notify the user of relaxation methods that take this into consideration.

[0647] This allows new fathers to receive specific child-rearing advice in real time that is tailored to their own behavior, environment, and emotional state, reducing the burden of child-rearing and supporting the harmonious development of their families.

[0648] (Example of a prompt)

[0649] "How do I help my baby relax while I'm getting him to sleep?"

[0650] "What are some easy ways to relax when you're stressed?"

[0651] "Please tell me the specific steps to make getting your child to sleep easier."

[0652] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0653] Step 1:

[0654] Collecting user information

[0655] The device collects calendar information, location data, and information about the software being used. Input data includes calendar information registered by the user on the device, location data obtained from the GPS module, and information about the applications being used. The device periodically obtains this data and temporarily stores the collected information. Specifically, it obtains schedule information from the calendar app, checks the user's current location from GPS data, and records the history of the applications being used.

[0656] Step 2:

[0657] Emotional state analysis

[0658] The device inputs the collected voice and facial expression data into an emotion engine, which outputs it as emotional data. The emotion engine uses voice analysis and facial recognition technology to analyze the user's emotional state. It receives voice data and facial expression images as input, and generates data representing stress levels and emotional states as output. Specifically, it analyzes voice recorded using a microphone and facial expressions captured with a camera.

[0659] Step 3:

[0660] Data Transfer

[0661] The device sends the collected calendar information, location data, information on the software used, and emotion data to the server. The input data is information stored in the device, and the output data is data packets sent to the server. Specifically, the device sends all collected data to the server at regular intervals.

[0662] Step 4:

[0663] Data storage

[0664] The server stores the received data in a database. Input data includes calendar information, location data, software used, and emotion data sent from the device, and the output is a database entry. Specifically, the server analyzes the received data, associates it with the user ID, and records it in the database.

[0665] Step 5:

[0666] Analysis of behavioral patterns and emotional states

[0667] The server analyzes the user's behavioral patterns and emotional state based on the received data. The input data includes past data and data from other users, and the output is the analysis results. Specifically, the server inputs the data into an AI model, which then analyzes the user's behavioral patterns and emotional state.

[0668] Step 6:

[0669] Generating Advice

[0670] The server generates parenting advice based on the results of analyzing behavioral patterns and emotional data. The input data are the results of behavioral pattern analysis and emotional state analysis, and the output is parenting advice. In concrete terms, the server uses the generative AI model to create parenting advice in text, image, and video format that is optimal for the user's condition.

[0671] Step 7:

[0672] Providing advice

[0673] The server sends the generated parenting advice to the user's device, which then notifies and displays it to the user. The generated parenting advice is input data, and the advice is displayed on the user's device as output. Specifically, the server sends the generated advice to the device at the appropriate time, and the device notifies the user via push notification, etc.

[0674] (Application example 2)

[0675] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0676] Today's new fathers often face many anxieties and questions about child-rearing. In particular, they lack advice tailored to their specific child-rearing situations and support that takes into account the father's own emotional state. This can increase stress and result in a decline in the quality of child-rearing. Because conventional systems do not provide customized advice based on emotional states and behavioral patterns, an effective solution to this problem is needed.

[0677] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting data from the user's terminal, means for analyzing the user's behavioral patterns based on the data, and means for customizing advice based on emotional data. This makes it possible to provide child-rearing advice that is suited to the user's specific behavioral patterns and emotional state.

[0678] "User's terminal" is a general term for a communication-enabled device used by a user, and mainly refers to a smartphone, smart glasses, a head-mounted display, or a robot.

[0679] "Data" refers to all information related to the user's behavior and environment, including calendar information, GPS data, information about the apps used, and emotional data generated from voice and facial expressions.

[0680] "Server" means a computer system on a network that receives and stores data, analyzes it, generates advice, and sends it to a user's device.

[0681] "Behavioral patterns" refer to specific behavioral patterns or tendencies derived from a user's past and present behavior.

[0682] "Emotion data" refers to information about the user's emotional state obtained by analyzing the user's voice and facial expressions.

[0683] "Parenting advice" refers to specific and practical guidance and suggestions regarding child-rearing that are generated based on the user's behavioral patterns and emotional state.

[0684] "Customization" refers to the process of tailoring advice content to a user's individual behavioral patterns and emotional state.

[0685] "Notification" refers to the act of sending childcare advice to the user's device in real time to inform the user.

[0686] This invention is a system that resolves the anxieties and doubts that new fathers face in child-rearing and provides optimal child-rearing advice in real time. The system consists of a user terminal, a server, and an emotion engine.

[0687] System configuration

[0688] User's device

[0689] The user's device is a communication-enabled device such as a smartphone, smart glasses, a head-mounted display, or a robot. The device collects the following data:

[0690] Calendar information: Get scheduled childcare activities and more.

[0691] GPS data: Obtaining the user's location.

[0692] App usage information: Obtain a history of apps used by the user.

[0693] Emotional data: The user's emotional state is obtained through analysis of voice and facial expressions.

[0694] Data collection and analysis

[0695] 1. Data Collection

[0696] The device periodically collects various data related to the user's behavior and environment. The emotion engine analyzes the user's voice and facial expressions to generate emotion data.

[0697] 2. Data Transfer

[0698] The collected data is sent to a server in real time.

[0699] Processing on the server

[0700] 1. Data storage and analysis

[0701] The server stores the received data in a database for each user. The stored data is used to analyze the user's behavioral patterns. The analysis is performed by comparing the data with past data and data from other users. The content of advice is also customized based on emotional data.

[0702] Hardware and software used

[0703] Hardware: Servers, databases, smartphones

[0704] Software: Python, API, TensorFlow, Django (or Flask), sentiment analysis engine

[0705] Generating and Serving Advice

[0706] 1. Advice Generation

[0707] The server generates parenting advice based on the analysis results. The advice is provided in text, video, image, and other formats. Based on the emotional data, the server customizes the advice to suit the user's emotional state.

[0708] 2. Advice Notice

[0709] The generated child-rearing advice is notified to the user's terminal in real time shortly before the time of the user's specific activity.

[0710] Specific examples

[0711] For example, if a user plans to put their child to bed at 8:00 PM, the device will collect that information and notify them of advice generated by the server at 7:45 PM. If the user's stress level is determined to be high, they will also be notified of relaxation techniques.

[0712] Prompt Sentence Examples

[0713] The user is in the following emotional state: Stress

[0714] Recent patterns of behavior include:

[0715] Calendar: Bedtime (20:00)

[0716] GPS Location: Home

[0717] App usage history: Parenting apps, relaxation apps

[0718] Generate specific parenting advice, including "5 effective ways to get your baby to sleep," to address any concerns or questions users may have. Also, provide relaxation advice if users are feeling stressed.

[0719] This invention allows new fathers to receive specific child-rearing advice in real time that is tailored to their own behavior, environment, and emotional state, reducing the burden of child-rearing and supporting the harmonious development of the family.

[0720] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0721] Step 1:

[0722] The device collects data related to the user's behavior and environment. Specifically, it acquires calendar information, GPS data, information on the apps used, and emotional data generated from voice and facial expressions. The input data is the user's calendar information, GPS location information, app usage history, voice data, and video data, and the output data is a set of collected data including this information.

[0723] Step 2:

[0724] The terminal transmits the collected data to the server in real time. The input data is the data collected in step 1, and the output data is the data transmitted to the server. The specific transmission operation uses a communication protocol such as an HTTP request or WebSocket.

[0725] Step 3:

[0726] The server stores the received data in a database. The input data is the data sent from the terminal, and the output data is the stored database entry. Specifically, it executes an INSERT statement against the database (e.g., MySQL or PostgreSQL).

[0727] Step 4:

[0728] The server analyzes the user's behavioral patterns based on the stored data. The input data is past data stored in the database and data from other users, and the output data is the analysis results of the behavioral patterns. Specifically, the data is analyzed using a machine learning model (e.g., TensorFlow or PyTorch).

[0729] Step 5:

[0730] The server generates advice based on the user's emotional data. The input data are the analysis results of behavioral patterns and emotional data, and the output data is the generated parenting advice. Specifically, the system uses an emotion analysis engine to generate prompt sentences, which are then input into the AI ​​model to obtain advice.

[0731] Step 6:

[0732] The server notifies the user's device of the generated parenting advice. The input data is the generated advice, and the output data is the notification sent to the device. Specifically, the advice is sent to the device using a push notification service (e.g., Firebase Cloud Messaging).

[0733] Users can receive real-time advice based on specific activity times, which can improve the quality of their child-rearing. This series of processing steps realizes a system that effectively solves many of the challenges new fathers face in child-rearing.

[0734] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0735] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0736] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0737] [Third embodiment]

[0738] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0739] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0740] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0741] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0742] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0743] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0744] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0745] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0746] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0747] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0748] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0749] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0750] This invention is a system that provides optimal child-rearing advice by eliminating the anxieties and doubts that new fathers face in child-rearing. This system uses the user's device and a server to collect and analyze data and provide specific child-rearing advice in real time.

[0751] Collecting user information

[0752] The device collects various data related to the user's behavior and environment, specifically, calendar information, GPS data, and information about the apps used, on a regular basis.

[0753] Specific examples

[0754] If a user has "Putting the child to bed (20:00)" scheduled on their smartphone calendar, the device will detect this information and use GPS data to confirm that the user is at home during that time.

[0755] Data Transfer

[0756] The collected data is sent from the device to a server in real time, including calendar information, GPS data, and app usage history.

[0757] Data storage and analysis

[0758] The server stores the received data in a database for each user. It also analyzes the user's behavioral patterns based on the accumulated data. The analysis is performed using an AI model, comparing past data with data from other users.

[0759] Specific examples

[0760] The server analyzes specific behavioral patterns when putting a child to sleep based on data from the past week, and generates effective advice by referencing parenting methods that other users have used successfully.

[0761] Generating Advice

[0762] The server generates parenting advice based on the results of behavioral pattern analysis. The advice is provided in text, video, image, and other formats.

[0763] Specific examples

[0764] The server generates advice including "five effective ways to put a baby to sleep," including the specific method of "gently patting the baby's tummy."

[0765] Providing advice

[0766] The generated child-rearing advice is sent to the user's device at an appropriate time, and the device notifies the user of the received advice and displays it.

[0767] Specific examples

[0768] At 15 minutes (19:45) before bedtime (20:00), the server sends the generated advice to the terminal, which then notifies the user.

[0769] This system allows new fathers to receive specific child-rearing advice in real time that is tailored to their own behavior and environment, reducing the burden of child-rearing and supporting the harmonious development of the family.

[0770] The processing flow will be explained below.

[0771] Step 1:

[0772] Collecting device information

[0773] The user's device collects calendar information, GPS data, and information on the apps they use. It detects childcare-related events (e.g., putting the baby to bed, feeding time) from the calendar information, identifies the user's current location using GPS data, and checks the usage history of childcare-related apps.

[0774] Step 2:

[0775] Sending data

[0776] The device sends the collected data in real time to a server, including calendar information, GPS data, and app usage history.

[0777] Step 3:

[0778] Data storage

[0779] The server stores the received data in a database for each user, and the accumulated data is used to analyze user behavior patterns.

[0780] Step 4:

[0781] Behavioral pattern analysis

[0782] The server analyzes the user's behavioral patterns based on past data and data from other users. It uses an AI model to extract the user's behavioral tendencies and habits and make predictions. It also compares the data with other users to identify parenting methods with a high success rate.

[0783] Step 5:

[0784] Generating Advice

[0785] The server generates parenting advice based on the results of the behavioral pattern analysis. The advice is provided in the form of text, video, images, etc.

[0786] Step 6:

[0787] Sending Advice

[0788] The server transmits the generated child-rearing advice to the user's terminal at an appropriate time.

[0789] Step 7:

[0790] Advice Notification

[0791] The device notifies and displays the received advice to the user, who can then check the specific parenting advice and take action based on it.

[0792] Example 1

[0793] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0794] In recent years, there has been a demand for support systems that can alleviate the anxieties and doubts that new fathers face in child-rearing and provide optimal child-rearing advice. For example, fathers with little experience in child-rearing may find it difficult to determine how to effectively put their children to sleep or what methods are optimal for daily child-rearing. However, existing child-rearing support systems lack the functionality to provide specific advice in real time based on a user's unique behavioral patterns and environmental information. The present invention aims to solve these problems and provide a system that allows new fathers to obtain specific child-rearing advice in real time that is tailored to their own behavior and environment.

[0795] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0796] In this invention, the server includes means for collecting calendar information, location information, and application usage history from the user's device, means for transmitting the collected data to the server in real time, means for storing the data received by the server in a database for each user, means for using a generative AI model to analyze the user's behavioral patterns based on the stored data, means for generating child-rearing advice based on the analysis results, and means for notifying the user's device of the generated child-rearing advice at an appropriate time, thereby making it possible to provide specific and effective child-rearing advice in real time based on the user's unique behavioral patterns and environmental information.

[0797] "User terminal" refers to an electronic device owned by a user, including a smartphone, tablet, or other device that can connect to the Internet.

[0798] "Calendar information" refers to schedule and event information that a user has registered in an electronic calendar.

[0799] "Location information" is data indicating the geographic location of a user obtained using a GPS function or other location measurement means.

[0800] "Application usage history" refers to history information of applications used by a user on a terminal, including specific usage time and activity content.

[0801] "Server" refers to the central processing unit that stores and analyzes collected data and generates and distributes parenting advice.

[0802] A "database" is a system for structuring and managing information stored on a server, including data records for each user.

[0803] A "generative AI model" refers to a program that uses machine learning or artificial intelligence techniques to analyze data and generate parenting advice.

[0804] "Real-time" refers to a process in which data is analyzed and processed almost immediately after it is collected.

[0805] "Behavioral patterns" refer to behavioral tendencies and characteristics analyzed based on a user's past actions and habits.

[0806] "Childcare advice" refers to instructions and suggestions regarding childcare generated based on the user's behavioral patterns and environmental information.

[0807] "Notification" refers to the process of sending messages or alerts from the server to the user's device to provide information to the user.

[0808] MODE FOR CARRYING OUT THE INVENTION

[0809] This system is designed to alleviate the anxieties and doubts that new fathers face in child-rearing and to provide optimal child-rearing advice. A specific embodiment of the system will be described below.

[0810] User behavior data collection

[0811] The user's device collects calendar information, location information, and application usage history. This data is collected using applications installed on smartphones and tablets. For example, the system obtains information such as "Putting kids to bed (20:00)" entered in the user's smartphone calendar. It also uses GPS data to confirm that the user is at home.

[0812] Data Transfer

[0813] The collected data is sent in real time from the device to a server using Wi-Fi or mobile data. The device sends packets containing calendar information, location information, and app usage history.

[0814] Data storage

[0815] The server stores the received data in a database for each individual user. The database is structured and designed to efficiently manage user behavior and environmental information.

[0816] Data analysis

[0817] The server analyzes the user's behavioral patterns based on the stored data. This analysis uses a generative AI model, which compares the user's past data with that of other users to extract the optimal behavioral patterns for the user.

[0818] Specific examples of prompts are as follows:

[0819] "Based on data from the past week, please extract the user's behavioral patterns when putting their child to sleep."

[0820] "Generate effective parenting advice based on other users' successful parenting methods."

[0821] Generating Advice

[0822] The server generates childcare advice based on the results of the behavioral pattern analysis. The advice is provided to the user in text, image, video, or other formats. For example, the server may generate advice including "five effective ways to get a baby to sleep," including the specific method of "gently patting the tummy."

[0823] Providing advice

[0824] The generated parenting advice is sent to the user's device at the appropriate time. The device notifies the user of the received advice and displays it. For example, the server sends the parenting advice to the device 15 minutes (19:45) before bedtime (20:00), and the device notifies the user of the information.

[0825] This system allows new fathers to receive specific child-rearing advice in real time that is tailored to their own behavior and environment, reducing the burden of child-rearing and supporting the harmonious development of the family.

[0826] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0827] Step 1:

[0828] User behavior data collection

[0829] Input: Data related to user behavior and environment (calendar information, location information, application usage history)

[0830] Specific behavior:

[0831] The device accesses the smartphone's calendar app to obtain event information. For example, it detects information that the user has registered in the calendar as "Putting the child to bed (20:00)."

[0832] The device uses a GPS sensor to determine where the user is at that time of day, specifically whether the user is at home.

[0833] The device obtains historical information about the apps the user is using and collects activities related to childcare (e.g., browsing history of childcare apps and websites).

[0834] Output: Collected data (calendar information, location information, application usage history)

[0835] Step 2:

[0836] Data Transfer

[0837] Input: Collected data (calendar information, location information, application usage history)

[0838] Specific behavior:

[0839] The device creates packets containing calendar, GPS, and app history data.

[0840] The device uses Wi-Fi or mobile data to send the created packets to the server.

[0841] Output: Data sent to the server

[0842] Step 3:

[0843] Data storage

[0844] Input: Data sent to the server (calendar information, location information, application usage history)

[0845] Specific behavior:

[0846] The server analyzes the received data and stores it as a data record in a dedicated database table for each user.

[0847] Output: Data stored in the database

[0848] Step 4:

[0849] Data analysis

[0850] Input: Data stored in the database (calendar information, location information, application usage history)

[0851] Specific behavior:

[0852] The server sends an analysis request to the generative AI model using a prompt sentence.

[0853] Example prompt: "Based on data from the past week, please identify patterns in how users put their children to bed."

[0854] The generative AI model returns the analysis results to the server, which then uses this to understand the user's behavioral patterns.

[0855] Output: Analysis results of behavioral patterns

[0856] Step 5:

[0857] Generating Advice

[0858] Input: Analysis results of behavioral patterns

[0859] Specific behavior:

[0860] The server sends prompts to the generative AI model to generate specific parenting advice.

[0861] Example prompt: "What are five effective ways to get your child to sleep?"

[0862] The generative AI model generates advice in the form of text, images, or videos and returns it to the server.

[0863] The server formats the advice it receives and presents it in a form suitable for the user.

[0864] Output: Generated parenting advice (in text, image, and video formats)

[0865] Step 6:

[0866] Providing advice

[0867] Input: Generated parenting advice (text, image, video format)

[0868] Specific behavior:

[0869] The server refers to the user's schedule and sends advice at the optimal time (for example, 15 minutes before putting the child to bed).

[0870] The device receives the advice and notifies the user using the notification function.

[0871] The device displays an appropriate UI screen so that the user can check the advice.

[0872] Output: Parenting advice received and confirmed by the user

[0873] (Application example 1)

[0874] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0875] There is a need to alleviate the anxieties and questions new fathers face when raising children, provide optimal childcare advice in real time, and facilitate the selection of childcare-related products in physical stores. However, conventional systems require users to manually search for information or navigate the store, which creates problems of burden and time-consuming childcare. Furthermore, there is a lack of a way to provide detailed advice in real time tailored to specific situations and locations.

[0876] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0877] In this invention, the server includes means for collecting data from a user's device, means for transmitting the data to the server, means for analyzing the user's behavioral patterns based on the data, means for generating child-rearing advice based on the behavioral pattern analysis, means for notifying the user's device of the child-rearing advice, and means for displaying the child-rearing advice and product information in the store using smart glasses. This makes it easier to obtain information and advice about child-rearing in real time in a physical store, thereby reducing the burden of child-rearing on the user.

[0878] "User" refers to individuals who use the system, especially new fathers.

[0879] "Device" refers to an electronic device used by a user, such as a smartphone or smart glasses.

[0880] "Data" refers to information collected from the device, such as calendar information, GPS data, and app usage history.

[0881] "Server" refers to a computer system for receiving and analyzing data.

[0882] "Behavioral patterns" refer to behavioral trends analyzed based on the user's past data and data from other users.

[0883] "Childcare advice" refers to advice on specific childcare methods and product selection provided based on an analysis of the user's behavioral patterns.

[0884] "Notification" refers to the act of sending childcare advice to the user's device and notifying them at the appropriate time.

[0885] "Smart glasses" refers to a wearable device that is worn by the user and is equipped with a display and camera.

[0886] "In-store" refers to the interior space of a physical store where childcare products are sold.

[0887] "Product information" refers to detailed descriptions of childcare-related products, how to use them, and advice about them.

[0888] This invention is a system that provides optimal childcare advice to new fathers by eliminating their concerns and questions about childcare. The system uses users' devices and a server to collect and analyze data and provide specific childcare advice in real time. It also has the ability to display childcare advice and product information using smart glasses in physical stores.

[0889] Collecting user information

[0890] The user's device collects various data related to the user's behavior and environment. Specifically, it periodically acquires calendar information, GPS data, and information about the apps used. For example, if a user has "Putting the kids to bed (8:00 PM)" registered on their smartphone calendar, the device will detect this information and use GPS data to confirm that the user is at home during that time.

[0891] Data Transfer

[0892] The collected data is sent from the device to a server in real time, including calendar information, GPS data, and app usage history.

[0893] Data storage and analysis

[0894] The server stores the received data in a database for each user. It also analyzes the user's behavioral patterns based on the accumulated data. The analysis is performed by comparing past data with data from other users and using a generative AI model (e.g., GTP-4). The server analyzes the user's specific behavioral patterns when putting their child to sleep based on data from the past week. It also generates effective advice by referring to the parenting methods that other users have used successfully.

[0895] Generating Advice

[0896] The server generates parenting advice based on the results of analyzing behavioral patterns. The advice is provided in text, video, image, and other formats. For example, the server may generate advice including "five effective ways to get a baby to sleep," including the specific method of "gently patting the baby's tummy."

[0897] Providing advice

[0898] The generated parenting advice is sent to the user's device or smart glasses at the appropriate time. The device or smart glasses notifies the user of the received advice and displays it. For example, at 19:45, 15 minutes before bedtime (20:00), the server sends the generated advice to the device, and the device notifies the user.

[0899] Use in physical stores

[0900] This system also uses smart glasses to provide childcare advice and product information within physical stores. As a user walks around a childcare store, the smart glasses detect the user's location and send it to a server. The server generates appropriate product information and childcare advice based on the product location information within the store and the user's data, and displays it on the smart glasses' display.

[0901] Specific examples

[0902] For example, if a user is looking for advice on "diaper changing," the server will display the location of related products (e.g., diapers, baby wipes) and show the features and usage of each product on the smart glasses. Also, if a user wants advice from a generative AI model using a prompt sentence, they can enter a sentence like the following:

[0903] Prompt Sentence Examples

[0904] I'm a new dad and I'm currently struggling with childcare. I have "putting my child to bed (8:00 PM)" scheduled on my calendar, and I'm usually at home during that time. It's hard to find products while raising my child. Could you recommend any products or give me some childcare advice?

[0905] This makes it easier to obtain information and advice about childcare in real time within a physical store, reducing the burden of childcare on users.

[0906] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0907] Step 1:

[0908] The user's device (smartphone or smart glasses) collects data related to the user's behavior and environment. Specifically, it acquires calendar information, GPS data, and information on the apps used. As input, it acquires information such as "Putting the child to bed (20:00)" that the user has registered in their smartphone calendar. As output, this data is stored on the device.

[0909] Step 2:

[0910] The device sends the collected data in real time to the server. The input includes calendar information, GPS data, and app usage history, and the server receives the information as output.

[0911] Step 3:

[0912] The server stores the received data in a database for each user. As input, there are multiple data sent from the terminal, and as output, the database entry corresponding to each user is updated.

[0913] Step 4:

[0914] The server analyzes the user's behavioral patterns based on the stored data. For the analysis, it references past data and data from other users and uses a generative AI model (e.g., GPT-4). Data from the past week and other users are provided as input, and the user's behavioral patterns are identified as output.

[0915] Step 5:

[0916] The server generates parenting advice based on the results of the behavioral pattern analysis. The generated advice is provided in text, video, or image format. The input includes the results of the behavioral pattern analysis, and the output generates specific parenting advice. For example, the generated advice might be "five effective ways to put your child to sleep."

[0917] Step 6:

[0918] The generated parenting advice is sent to the user's device or smart glasses. The device or smart glasses notifies and displays the received advice to the user. The generated parenting advice is sent from the server as input, and an alert or notification is displayed on the user's device as output.

[0919] Step 7:

[0920] As a user walks around a baby care store, the smart glasses detect the user's location and send it to a server. The input includes GPS data from within the store, and the output conveys the user's real-time location to the server.

[0921] Step 8:

[0922] The server generates appropriate product information and parenting advice based on the product location information in the store and the user data, and displays it on the smart glasses display. The input includes the user's location information and related data, and the output is the product information and parenting advice displayed on the smart glasses.

[0923] The above are the specific processing steps for carrying out the present invention, which make it easier for users to obtain information and advice on childcare in real time, and enable them to smoothly select childcare-related products in physical stores.

[0924] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0925] This invention is a system that provides optimal child-rearing advice by eliminating the anxieties and doubts that new fathers face in child-rearing. This system uses the user's device, a server, and an emotion engine to collect and analyze data and provide specific child-rearing advice in real time.

[0926] Collecting user information

[0927] The device collects various data related to the user's behavior and environment. Specifically, it periodically acquires calendar information, GPS data, and information on the apps used. The device also has an emotion engine that analyzes the user's voice and facial expressions to generate emotion data.

[0928] Specific examples

[0929] If a user has "Putting the child to bed (8:00 PM)" scheduled on their smartphone calendar, the device will detect this information. It will also use GPS data to confirm that the user is at home during that time. Furthermore, the emotion engine will analyze the user's tone of voice and facial expressions to determine whether the user is feeling stressed.

[0930] Data Transfer

[0931] The collected data is sent from the device to a server in real time, including calendar information, GPS data, app usage history, and emotional data.

[0932] Data storage and analysis

[0933] The server stores the received data in a database for each user. It also analyzes the user's behavioral patterns based on the accumulated data. The analysis is performed using an AI model, comparing past data with data from other users. Furthermore, emotional data is used to customize the content of advice.

[0934] Specific examples

[0935] The server analyzes specific behavioral patterns when putting the user to sleep based on data from the past week, and if the user is feeling stressed, it generates advice including relaxation techniques.

[0936] Generating Advice

[0937] The server generates parenting advice based on the results of the behavioral pattern analysis. The advice is provided in text, video, image, and other formats. Based on the emotional data, appropriate advice is added according to the user's emotional state.

[0938] Specific examples

[0939] The server generates advice including "5 effective ways to put a child to sleep," including the specific method of "gently patting the child's stomach." Furthermore, if the user is feeling stressed, it adds a relaxation technique such as "take a deep breath before putting the child to sleep."

[0940] Providing advice

[0941] The generated child-rearing advice is sent to the user's device at an appropriate time, and the device notifies the user of the received advice and displays it.

[0942] Specific examples

[0943] The server sends the generated advice to the device 15 minutes (19:45) before bedtime (20:00), and the device notifies the user. If the user's stress level is high, the device also provides relaxation advice taking that into account.

[0944] This system allows new fathers to receive specific child-rearing advice in real time based on their own behavior, environment, and emotional state, reducing the burden of child-rearing and supporting the harmonious development of the family.

[0945] The processing flow will be explained below.

[0946] Step 1:

[0947] Collecting device information

[0948] The user's device periodically collects calendar information, GPS data, and information about the apps they use. It also uses an emotion engine to analyze the user's voice and facial expressions to generate emotion data. This information is important for understanding the user's behavior and emotional state.

[0949] Specific examples

[0950] The device detects that "Putting the child to bed (20:00)" is registered on the user's calendar. GPS data confirms that the user is at home during that time. The emotion engine analyzes the user's tone of voice and facial expression and determines that the user's stress level is high.

[0951] Step 2:

[0952] Sending data

[0953] The device transmits the collected calendar information, GPS data, history of app usage, and emotion data to the server in real time.

[0954] Step 3:

[0955] Data storage

[0956] The server stores the received data in a database for each user, which is used for further analysis and advice generation.

[0957] Step 4:

[0958] Behavioral pattern analysis

[0959] The server analyzes the user's accumulated data, compares past data with that of other users, extracts the user's behavioral patterns, and makes predictions. Advanced analysis is performed using AI models.

[0960] Specific examples

[0961] The server analyzes calendar data from the past week to determine whether the user tends to put their child to bed at 8 p.m., and also uses emotional data to determine whether the user tends to feel stressed when putting their child to bed.

[0962] Step 5:

[0963] Generating Advice

[0964] The server generates parenting advice tailored to the user based on the analysis of the behavioral patterns and emotional data. The advice is customized according to the user's behavior and emotional state.

[0965] Specific examples

[0966] The server generates advice including "5 effective ways to put a child to sleep," including "gently patting the tummy" as one of the suggestions. Furthermore, considering that the user is feeling stressed, the server adds "taking deep breaths to calm the mind."

[0967] Step 6:

[0968] Sending Advice

[0969] The server transmits the generated child-rearing advice to the user's terminal at an appropriate time.

[0970] Step 7:

[0971] Advice Notification

[0972] The terminal notifies the user of the received advice and displays it, allowing the user to take action based on the advice.

[0973] Specific examples

[0974] The server sends the generated advice to the device 15 minutes before bedtime at 8:00 PM (7:45 PM). The device notifies the user of the advice and displays it. If the user is feeling stressed, the device also provides additional advice on relaxation techniques.

[0975] Through these steps, the system enables new fathers to receive optimal child-rearing advice and effectively resolves their anxieties and questions about child-rearing.

[0976] Example 2

[0977] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0978] To alleviate the anxieties and doubts that new fathers face in child-rearing and provide optimal child-rearing advice, it is necessary to understand the behavior and emotional state of each user and provide specific advice based on that in real time. However, conventional systems have difficulty generating advice that fully reflects each user's individual behavioral patterns and emotional state, resulting in the problem that the advice provided is general and not specific or effective.

[0979] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0980] In this invention, the server includes means for collecting calendar information, location data, and information on software used from the user's device, means for analyzing the collected data to grasp the user's emotional state, means for analyzing the user's behavioral patterns based on the data, means for generating child-rearing advice based on the analysis of the behavioral patterns and emotional state, and means for notifying the user's device of the child-rearing advice, thereby making it possible to provide specific and effective child-rearing advice based on the behavior and emotional state of each individual user in real time.

[0981] A "terminal" is an electronic device used by a user that has functions such as information collection, display, and communication.

[0982] "Calendar information" refers to data about events and schedules that a user has entered into a calendar application on the terminal.

[0983] "Location data" refers to information about a user's geographic location obtained by the user's device, and is collected via a GPS system or the like.

[0984] "Information about software used" is data related to the usage history and usage status of applications used by the user on the terminal.

[0985] "Emotional state" refers to the emotions and psychological state of a user, and is estimated using technologies such as voice analysis and facial expression recognition.

[0986] A "behavioral pattern" is a certain behavioral pattern or habit obtained as a result of analyzing a user's past behavior and behavioral tendencies.

[0987] "Childcare advice" is information such as specific instructions, suggestions, and advice regarding childcare, and is generated based on the user's behavioral patterns and emotional state.

[0988] A "server" is a computer system that communicates with terminals via a network, stores data, analyzes, processes data, and provides information.

[0989] "Means of collection" refers to the functions and processes for obtaining various data from the device (calendar information, location data, information on software used).

[0990] "Means of analysis" refers to the functions and processes for analyzing and processing the user's behavioral patterns and emotional state based on the collected data.

[0991] The "notification means" refers to a function or process for sending the generated child-rearing advice to the user's terminal and notifying the user.

[0992] This invention is a system that provides optimal child-rearing advice by eliminating the anxieties and doubts that new fathers face in child-rearing. This system utilizes the user's device, a server, and an emotion engine to collect and analyze data and provide specific child-rearing advice in real time.

[0993] Collecting user information

[0994] The user's device is equipped with hardware and software for collecting various data, including a calendar application, a GPS module, and software for monitoring the usage of various applications. It also includes an emotion engine for analyzing the user's voice and facial expressions.

[0995] As a concrete example of the "Mode for Carrying Out the Invention," consider a case where a user has entered "Putting the child to bed (20:00)" in their smartphone calendar. In this system, the device detects this information and simultaneously confirms via GPS data that the user is at home at that time. Furthermore, the emotion engine analyzes the user's tone of voice and facial expression to determine their stress level.

[0996] Data Transfer and Storage

[0997] The collected data is sent in real time from the user's device to a server, including calendar information, GPS data, app usage history, and emotional data.

[0998] The server stores the received data in a database for each user. The stored data is managed in a format linked to the user ID and is later used to analyze behavioral patterns.

[0999] Analyzing data and generating advice

[1000] The server uses an AI model based on the accumulated data to analyze the user's behavioral patterns. This analysis compares past data with other users' data to obtain highly accurate results. It also uses emotional data to understand the user's emotional state and customize the advice provided.

[1001] For example, the server analyzes specific behavioral patterns when putting a child to bed based on data from the past week, and if the user is experiencing high stress levels, generates advice including relaxation techniques.

[1002] The server generates parenting advice based on the analysis results. This advice is provided in text, image, video, and other formats. For example, advice can be generated that includes "five effective ways to put your child to sleep," including the specific method of "gently patting the child's tummy." Furthermore, if the user is feeling stressed, the server can add relaxation tips, such as "take a deep breath before putting the child to sleep."

[1003] Providing advice

[1004] The generated childcare advice is sent to the user's device at the appropriate time. The device notifies the user of the received advice and displays it. As a specific example, the server sends the generated advice to the device 15 minutes (19:45) before bedtime (20:00), and the device notifies the user. At this time, if the user's emotional data indicates a high stress level, the device will also notify the user of relaxation methods that take this into consideration.

[1005] This allows new fathers to receive specific child-rearing advice in real time that is tailored to their own behavior, environment, and emotional state, reducing the burden of child-rearing and supporting the harmonious development of their families.

[1006] (Example of a prompt)

[1007] "How do I help my baby relax while I'm getting him to sleep?"

[1008] "What are some easy ways to relax when you're stressed?"

[1009] "Please tell me the specific steps to make getting your child to sleep easier."

[1010] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1011] Step 1:

[1012] Collecting user information

[1013] The device collects calendar information, location data, and information about the software being used. Input data includes calendar information registered by the user on the device, location data obtained from the GPS module, and information about the applications being used. The device periodically obtains this data and temporarily stores the collected information. Specifically, it obtains schedule information from the calendar app, checks the user's current location from GPS data, and records the history of the applications being used.

[1014] Step 2:

[1015] Emotional state analysis

[1016] The device inputs the collected voice and facial expression data into an emotion engine, which outputs it as emotional data. The emotion engine uses voice analysis and facial recognition technology to analyze the user's emotional state. It receives voice data and facial expression images as input, and generates data representing stress levels and emotional states as output. Specifically, it analyzes voice recorded using a microphone and facial expressions captured with a camera.

[1017] Step 3:

[1018] Data Transfer

[1019] The device sends the collected calendar information, location data, information on the software used, and emotion data to the server. The input data is information stored in the device, and the output data is data packets sent to the server. Specifically, the device sends all collected data to the server at regular intervals.

[1020] Step 4:

[1021] Data storage

[1022] The server stores the received data in a database. Input data includes calendar information, location data, software used, and emotion data sent from the device, and the output is a database entry. Specifically, the server analyzes the received data, associates it with the user ID, and records it in the database.

[1023] Step 5:

[1024] Analysis of behavioral patterns and emotional states

[1025] The server analyzes the user's behavioral patterns and emotional state based on the received data. The input data includes past data and data from other users, and the output is the analysis results. Specifically, the server inputs the data into an AI model, which then analyzes the user's behavioral patterns and emotional state.

[1026] Step 6:

[1027] Generating Advice

[1028] The server generates parenting advice based on the results of analyzing behavioral patterns and emotional data. The input data are the results of behavioral pattern analysis and emotional state analysis, and the output is parenting advice. In concrete terms, the server uses the generative AI model to create parenting advice in text, image, and video format that is optimal for the user's condition.

[1029] Step 7:

[1030] Providing advice

[1031] The server sends the generated parenting advice to the user's device, which then notifies and displays it to the user. The generated parenting advice is input data, and the advice is displayed on the user's device as output. Specifically, the server sends the generated advice to the device at the appropriate time, and the device notifies the user via push notification, etc.

[1032] (Application example 2)

[1033] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1034] Today's new fathers often face many anxieties and questions about child-rearing. In particular, they lack advice tailored to their specific child-rearing situations and support that takes into account the father's own emotional state. This can increase stress and result in a decline in the quality of child-rearing. Because conventional systems do not provide customized advice based on emotional states and behavioral patterns, an effective solution to this problem is needed.

[1035] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting data from the user's terminal, means for analyzing the user's behavioral patterns based on the data, and means for customizing advice based on emotional data. This makes it possible to provide child-rearing advice that is suited to the user's specific behavioral patterns and emotional state.

[1036] "User's terminal" is a general term for a communication-enabled device used by a user, and mainly refers to a smartphone, smart glasses, a head-mounted display, or a robot.

[1037] "Data" refers to all information related to the user's behavior and environment, including calendar information, GPS data, information about the apps used, and emotional data generated from voice and facial expressions.

[1038] "Server" means a computer system on a network that receives and stores data, analyzes it, generates advice, and sends it to a user's device.

[1039] "Behavioral patterns" refer to specific behavioral patterns or tendencies derived from a user's past and present behavior.

[1040] "Emotion data" refers to information about the user's emotional state obtained by analyzing the user's voice and facial expressions.

[1041] "Parenting advice" refers to specific and practical guidance and suggestions regarding child-rearing that are generated based on the user's behavioral patterns and emotional state.

[1042] "Customization" refers to the process of tailoring advice content to a user's individual behavioral patterns and emotional state.

[1043] "Notification" refers to the act of sending childcare advice to the user's device in real time to inform the user.

[1044] This invention is a system that resolves the anxieties and doubts that new fathers face in child-rearing and provides optimal child-rearing advice in real time. The system consists of a user terminal, a server, and an emotion engine.

[1045] System configuration

[1046] User's device

[1047] The user's device is a communication-enabled device such as a smartphone, smart glasses, a head-mounted display, or a robot. The device collects the following data:

[1048] Calendar information: Get scheduled childcare activities and more.

[1049] GPS data: Obtaining the user's location.

[1050] App usage information: Obtain a history of apps used by the user.

[1051] Emotional data: The user's emotional state is obtained through analysis of voice and facial expressions.

[1052] Data collection and analysis

[1053] 1. Data Collection

[1054] The device periodically collects various data related to the user's behavior and environment. The emotion engine analyzes the user's voice and facial expressions to generate emotion data.

[1055] 2. Data Transfer

[1056] The collected data is sent to a server in real time.

[1057] Processing on the server

[1058] 1. Data storage and analysis

[1059] The server stores the received data in a database for each user. The stored data is used to analyze the user's behavioral patterns. The analysis is performed by comparing the data with past data and data from other users. The content of advice is also customized based on emotional data.

[1060] Hardware and software used

[1061] Hardware: Servers, databases, smartphones

[1062] Software: Python, API, TensorFlow, Django (or Flask), sentiment analysis engine

[1063] Generating and Serving Advice

[1064] 1. Advice Generation

[1065] The server generates parenting advice based on the analysis results. The advice is provided in text, video, image, and other formats. Based on the emotional data, the server customizes the advice to suit the user's emotional state.

[1066] 2. Advice Notice

[1067] The generated child-rearing advice is notified to the user's terminal in real time shortly before the time of the user's specific activity.

[1068] Specific examples

[1069] For example, if a user plans to put their child to bed at 8:00 PM, the device will collect that information and notify them of advice generated by the server at 7:45 PM. If the user's stress level is determined to be high, they will also be notified of relaxation techniques.

[1070] Prompt Sentence Examples

[1071] The user is in the following emotional state: Stress

[1072] Recent patterns of behavior include:

[1073] Calendar: Bedtime (20:00)

[1074] GPS Location: Home

[1075] App usage history: Parenting apps, relaxation apps

[1076] Generate specific parenting advice, including "5 effective ways to get your baby to sleep," to address any concerns or questions users may have. Also, provide relaxation advice if users are feeling stressed.

[1077] This invention allows new fathers to receive specific child-rearing advice in real time that is tailored to their own behavior, environment, and emotional state, reducing the burden of child-rearing and supporting the harmonious development of the family.

[1078] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1079] Step 1:

[1080] The device collects data related to the user's behavior and environment. Specifically, it acquires calendar information, GPS data, information on the apps used, and emotional data generated from voice and facial expressions. The input data is the user's calendar information, GPS location information, app usage history, voice data, and video data, and the output data is a set of collected data including this information.

[1081] Step 2:

[1082] The terminal transmits the collected data to the server in real time. The input data is the data collected in step 1, and the output data is the data transmitted to the server. The specific transmission operation uses a communication protocol such as an HTTP request or WebSocket.

[1083] Step 3:

[1084] The server stores the received data in a database. The input data is the data sent from the terminal, and the output data is the stored database entry. Specifically, it executes an INSERT statement against the database (e.g., MySQL or PostgreSQL).

[1085] Step 4:

[1086] The server analyzes the user's behavioral patterns based on the stored data. The input data is past data stored in the database and data from other users, and the output data is the analysis results of the behavioral patterns. Specifically, the data is analyzed using a machine learning model (e.g., TensorFlow or PyTorch).

[1087] Step 5:

[1088] The server generates advice based on the user's emotional data. The input data are the analysis results of behavioral patterns and emotional data, and the output data is the generated parenting advice. Specifically, the system uses an emotion analysis engine to generate prompt sentences, which are then input into the AI ​​model to obtain advice.

[1089] Step 6:

[1090] The server notifies the user's device of the generated parenting advice. The input data is the generated advice, and the output data is the notification sent to the device. Specifically, the advice is sent to the device using a push notification service (e.g., Firebase Cloud Messaging).

[1091] Users can receive real-time advice based on specific activity times, which can improve the quality of their child-rearing. This series of processing steps realizes a system that effectively solves many of the challenges new fathers face in child-rearing.

[1092] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1093] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1094] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1095] [Fourth embodiment]

[1096] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1097] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1098] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1099] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1100] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1101] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1102] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1103] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1104] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1105] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1106] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1107] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1108] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1109] This invention is a system that provides optimal child-rearing advice by eliminating the anxieties and doubts that new fathers face in child-rearing. This system uses the user's device and a server to collect and analyze data and provide specific child-rearing advice in real time.

[1110] Collecting user information

[1111] The device collects various data related to the user's behavior and environment, specifically, calendar information, GPS data, and information about the apps used, on a regular basis.

[1112] Specific examples

[1113] If a user has "Putting the child to bed (20:00)" scheduled on their smartphone calendar, the device will detect this information and use GPS data to confirm that the user is at home during that time.

[1114] Data Transfer

[1115] The collected data is sent from the device to a server in real time, including calendar information, GPS data, and app usage history.

[1116] Data storage and analysis

[1117] The server stores the received data in a database for each user. It also analyzes the user's behavioral patterns based on the accumulated data. The analysis is performed using an AI model, comparing past data with data from other users.

[1118] Specific examples

[1119] The server analyzes specific behavioral patterns when putting a child to sleep based on data from the past week, and generates effective advice by referencing parenting methods that other users have used successfully.

[1120] Generating Advice

[1121] The server generates parenting advice based on the results of behavioral pattern analysis. The advice is provided in text, video, image, and other formats.

[1122] Specific examples

[1123] The server generates advice including "five effective ways to put a baby to sleep," including the specific method of "gently patting the baby's tummy."

[1124] Providing advice

[1125] The generated child-rearing advice is sent to the user's device at an appropriate time, and the device notifies the user of the received advice and displays it.

[1126] Specific examples

[1127] At 15 minutes (19:45) before bedtime (20:00), the server sends the generated advice to the terminal, which then notifies the user.

[1128] This system allows new fathers to receive specific child-rearing advice in real time that is tailored to their own behavior and environment, reducing the burden of child-rearing and supporting the harmonious development of the family.

[1129] The processing flow will be explained below.

[1130] Step 1:

[1131] Collecting device information

[1132] The user's device collects calendar information, GPS data, and information on the apps they use. It detects childcare-related events (e.g., putting the baby to bed, feeding time) from the calendar information, identifies the user's current location using GPS data, and checks the usage history of childcare-related apps.

[1133] Step 2:

[1134] Sending data

[1135] The device sends the collected data in real time to a server, including calendar information, GPS data, and app usage history.

[1136] Step 3:

[1137] Data storage

[1138] The server stores the received data in a database for each user, and the accumulated data is used to analyze user behavior patterns.

[1139] Step 4:

[1140] Behavioral pattern analysis

[1141] The server analyzes the user's behavioral patterns based on past data and data from other users. It uses an AI model to extract the user's behavioral tendencies and habits and make predictions. It also compares the data with other users to identify parenting methods with a high success rate.

[1142] Step 5:

[1143] Generating Advice

[1144] The server generates parenting advice based on the results of the behavioral pattern analysis. The advice is provided in the form of text, video, images, etc.

[1145] Step 6:

[1146] Sending Advice

[1147] The server transmits the generated child-rearing advice to the user's terminal at an appropriate time.

[1148] Step 7:

[1149] Advice Notification

[1150] The device notifies and displays the received advice to the user, who can then check the specific parenting advice and take action based on it.

[1151] Example 1

[1152] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1153] In recent years, there has been a demand for support systems that can alleviate the anxieties and doubts that new fathers face in child-rearing and provide optimal child-rearing advice. For example, fathers with little experience in child-rearing may find it difficult to determine how to effectively put their children to sleep or what methods are optimal for daily child-rearing. However, existing child-rearing support systems lack the functionality to provide specific advice in real time based on a user's unique behavioral patterns and environmental information. The present invention aims to solve these problems and provide a system that allows new fathers to obtain specific child-rearing advice in real time that is tailored to their own behavior and environment.

[1154] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1155] In this invention, the server includes means for collecting calendar information, location information, and application usage history from the user's device, means for transmitting the collected data to the server in real time, means for storing the data received by the server in a database for each user, means for using a generative AI model to analyze the user's behavioral patterns based on the stored data, means for generating child-rearing advice based on the analysis results, and means for notifying the user's device of the generated child-rearing advice at an appropriate time, thereby making it possible to provide specific and effective child-rearing advice in real time based on the user's unique behavioral patterns and environmental information.

[1156] "User terminal" refers to an electronic device owned by a user, including a smartphone, tablet, or other device that can connect to the Internet.

[1157] "Calendar information" refers to schedule and event information that a user has registered in an electronic calendar.

[1158] "Location information" is data indicating the geographic location of a user obtained using a GPS function or other location measurement means.

[1159] "Application usage history" refers to history information of applications used by a user on a terminal, including specific usage time and activity content.

[1160] "Server" refers to the central processing unit that stores and analyzes collected data and generates and distributes parenting advice.

[1161] A "database" is a system for structuring and managing information stored on a server, including data records for each user.

[1162] A "generative AI model" refers to a program that uses machine learning or artificial intelligence techniques to analyze data and generate parenting advice.

[1163] "Real-time" refers to a process in which data is analyzed and processed almost immediately after it is collected.

[1164] "Behavioral patterns" refer to behavioral tendencies and characteristics analyzed based on a user's past actions and habits.

[1165] "Childcare advice" refers to instructions and suggestions regarding childcare generated based on the user's behavioral patterns and environmental information.

[1166] "Notification" refers to the process of sending messages or alerts from the server to the user's device to provide information to the user.

[1167] MODE FOR CARRYING OUT THE INVENTION

[1168] This system is designed to alleviate the anxieties and doubts that new fathers face in child-rearing and to provide optimal child-rearing advice. A specific embodiment of the system will be described below.

[1169] User behavior data collection

[1170] The user's device collects calendar information, location information, and application usage history. This data is collected using applications installed on smartphones and tablets. For example, the system obtains information such as "Putting kids to bed (20:00)" entered in the user's smartphone calendar. It also uses GPS data to confirm that the user is at home.

[1171] Data Transfer

[1172] The collected data is sent in real time from the device to a server using Wi-Fi or mobile data. The device sends packets containing calendar information, location information, and app usage history.

[1173] Data storage

[1174] The server stores the received data in a database for each individual user. The database is structured and designed to efficiently manage user behavior and environmental information.

[1175] Data analysis

[1176] The server analyzes the user's behavioral patterns based on the stored data. This analysis uses a generative AI model, which compares the user's past data with that of other users to extract the optimal behavioral patterns for the user.

[1177] Specific examples of prompts are as follows:

[1178] "Based on data from the past week, please extract the user's behavioral patterns when putting their child to sleep."

[1179] "Generate effective parenting advice based on other users' successful parenting methods."

[1180] Generating Advice

[1181] The server generates childcare advice based on the results of the behavioral pattern analysis. The advice is provided to the user in text, image, video, or other formats. For example, the server may generate advice including "five effective ways to get a baby to sleep," including the specific method of "gently patting the tummy."

[1182] Providing advice

[1183] The generated parenting advice is sent to the user's device at the appropriate time. The device notifies the user of the received advice and displays it. For example, the server sends the parenting advice to the device 15 minutes (19:45) before bedtime (20:00), and the device notifies the user of the information.

[1184] This system allows new fathers to receive specific child-rearing advice in real time that is tailored to their own behavior and environment, reducing the burden of child-rearing and supporting the harmonious development of the family.

[1185] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1186] Step 1:

[1187] User behavior data collection

[1188] Input: Data related to user behavior and environment (calendar information, location information, application usage history)

[1189] Specific behavior:

[1190] The device accesses the smartphone's calendar app to obtain event information. For example, it detects information that the user has registered in the calendar as "Putting the child to bed (20:00)."

[1191] The device uses a GPS sensor to determine where the user is at that time of day, specifically whether the user is at home.

[1192] The device obtains historical information about the apps the user is using and collects activities related to childcare (e.g., browsing history of childcare apps and websites).

[1193] Output: Collected data (calendar information, location information, application usage history)

[1194] Step 2:

[1195] Data Transfer

[1196] Input: Collected data (calendar information, location information, application usage history)

[1197] Specific behavior:

[1198] The device creates packets containing calendar, GPS, and app history data.

[1199] The device uses Wi-Fi or mobile data to send the created packets to the server.

[1200] Output: Data sent to the server

[1201] Step 3:

[1202] Data storage

[1203] Input: Data sent to the server (calendar information, location information, application usage history)

[1204] Specific behavior:

[1205] The server analyzes the received data and stores it as a data record in a dedicated database table for each user.

[1206] Output: Data stored in the database

[1207] Step 4:

[1208] Data analysis

[1209] Input: Data stored in the database (calendar information, location information, application usage history)

[1210] Specific behavior:

[1211] The server sends an analysis request to the generative AI model using a prompt sentence.

[1212] Example prompt: "Based on data from the past week, please identify patterns in how users put their children to bed."

[1213] The generative AI model returns the analysis results to the server, which then uses this to understand the user's behavioral patterns.

[1214] Output: Analysis results of behavioral patterns

[1215] Step 5:

[1216] Generating Advice

[1217] Input: Analysis results of behavioral patterns

[1218] Specific behavior:

[1219] The server sends prompts to the generative AI model to generate specific parenting advice.

[1220] Example prompt: "What are five effective ways to get your child to sleep?"

[1221] The generative AI model generates advice in the form of text, images, or videos and returns it to the server.

[1222] The server formats the advice it receives and presents it in a form suitable for the user.

[1223] Output: Generated parenting advice (in text, image, and video formats)

[1224] Step 6:

[1225] Providing advice

[1226] Input: Generated parenting advice (text, image, video format)

[1227] Specific behavior:

[1228] The server refers to the user's schedule and sends advice at the optimal time (for example, 15 minutes before putting the child to bed).

[1229] The device receives the advice and notifies the user using the notification function.

[1230] The device displays an appropriate UI screen so that the user can check the advice.

[1231] Output: Parenting advice received and confirmed by the user

[1232] (Application example 1)

[1233] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1234] There is a need to alleviate the anxieties and questions new fathers face when raising children, provide optimal childcare advice in real time, and facilitate the selection of childcare-related products in physical stores. However, conventional systems require users to manually search for information or navigate the store, which creates problems of burden and time-consuming childcare. Furthermore, there is a lack of a way to provide detailed advice in real time tailored to specific situations and locations.

[1235] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1236] In this invention, the server includes means for collecting data from a user's device, means for transmitting the data to the server, means for analyzing the user's behavioral patterns based on the data, means for generating child-rearing advice based on the behavioral pattern analysis, means for notifying the user's device of the child-rearing advice, and means for displaying the child-rearing advice and product information in the store using smart glasses. This makes it easier to obtain information and advice about child-rearing in real time in a physical store, thereby reducing the burden of child-rearing on the user.

[1237] "User" refers to individuals who use the system, especially new fathers.

[1238] "Device" refers to an electronic device used by a user, such as a smartphone or smart glasses.

[1239] "Data" refers to information collected from the device, such as calendar information, GPS data, and app usage history.

[1240] "Server" refers to a computer system for receiving and analyzing data.

[1241] "Behavioral patterns" refer to behavioral trends analyzed based on the user's past data and data from other users.

[1242] "Childcare advice" refers to advice on specific childcare methods and product selection provided based on an analysis of the user's behavioral patterns.

[1243] "Notification" refers to the act of sending childcare advice to the user's device and notifying them at the appropriate time.

[1244] "Smart glasses" refers to a wearable device that is worn by the user and is equipped with a display and camera.

[1245] "In-store" refers to the interior space of a physical store where childcare products are sold.

[1246] "Product information" refers to detailed descriptions of childcare-related products, how to use them, and advice about them.

[1247] This invention is a system that provides optimal childcare advice to new fathers by eliminating their concerns and questions about childcare. The system uses users' devices and a server to collect and analyze data and provide specific childcare advice in real time. It also has the ability to display childcare advice and product information using smart glasses in physical stores.

[1248] Collecting user information

[1249] The user's device collects various data related to the user's behavior and environment. Specifically, it periodically acquires calendar information, GPS data, and information about the apps used. For example, if a user has "Putting the kids to bed (8:00 PM)" registered on their smartphone calendar, the device will detect this information and use GPS data to confirm that the user is at home during that time.

[1250] Data Transfer

[1251] The collected data is sent from the device to a server in real time, including calendar information, GPS data, and app usage history.

[1252] Data storage and analysis

[1253] The server stores the received data in a database for each user. It also analyzes the user's behavioral patterns based on the accumulated data. The analysis is performed by comparing past data with data from other users and using a generative AI model (e.g., GTP-4). The server analyzes the user's specific behavioral patterns when putting their child to sleep based on data from the past week. It also generates effective advice by referring to the parenting methods that other users have used successfully.

[1254] Generating Advice

[1255] The server generates parenting advice based on the results of analyzing behavioral patterns. The advice is provided in text, video, image, and other formats. For example, the server may generate advice including "five effective ways to get a baby to sleep," including the specific method of "gently patting the baby's tummy."

[1256] Providing advice

[1257] The generated parenting advice is sent to the user's device or smart glasses at the appropriate time. The device or smart glasses notifies the user of the received advice and displays it. For example, at 19:45, 15 minutes before bedtime (20:00), the server sends the generated advice to the device, and the device notifies the user.

[1258] Use in physical stores

[1259] This system also uses smart glasses to provide childcare advice and product information within physical stores. As a user walks around a childcare store, the smart glasses detect the user's location and send it to a server. The server generates appropriate product information and childcare advice based on the product location information within the store and the user's data, and displays it on the smart glasses' display.

[1260] Specific examples

[1261] For example, if a user is looking for advice on "diaper changing," the server will display the location of related products (e.g., diapers, baby wipes) and show the features and usage of each product on the smart glasses. Also, if a user wants advice from a generative AI model using a prompt sentence, they can enter a sentence like the following:

[1262] Prompt Sentence Examples

[1263] I'm a new dad and I'm currently struggling with childcare. I have "putting my child to bed (8:00 PM)" scheduled on my calendar, and I'm usually at home during that time. It's hard to find products while raising my child. Could you recommend any products or give me some childcare advice?

[1264] This makes it easier to obtain information and advice about childcare in real time within a physical store, reducing the burden of childcare on users.

[1265] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1266] Step 1:

[1267] The user's device (smartphone or smart glasses) collects data related to the user's behavior and environment. Specifically, it acquires calendar information, GPS data, and information on the apps used. As input, it acquires information such as "Putting the child to bed (20:00)" that the user has registered in their smartphone calendar. As output, this data is stored on the device.

[1268] Step 2:

[1269] The device sends the collected data in real time to the server. The input includes calendar information, GPS data, and app usage history, and the server receives the information as output.

[1270] Step 3:

[1271] The server stores the received data in a database for each user. As input, there are multiple data sent from the terminal, and as output, the database entry corresponding to each user is updated.

[1272] Step 4:

[1273] The server analyzes the user's behavioral patterns based on the stored data. For the analysis, it references past data and data from other users and uses a generative AI model (e.g., GPT-4). Data from the past week and other users are provided as input, and the user's behavioral patterns are identified as output.

[1274] Step 5:

[1275] The server generates parenting advice based on the results of the behavioral pattern analysis. The generated advice is provided in text, video, or image format. The input includes the results of the behavioral pattern analysis, and the output generates specific parenting advice. For example, the generated advice might be "five effective ways to put your child to sleep."

[1276] Step 6:

[1277] The generated parenting advice is sent to the user's device or smart glasses. The device or smart glasses notifies and displays the received advice to the user. The generated parenting advice is sent from the server as input, and an alert or notification is displayed on the user's device as output.

[1278] Step 7:

[1279] As a user walks around a baby care store, the smart glasses detect the user's location and send it to a server. The input includes GPS data from within the store, and the output conveys the user's real-time location to the server.

[1280] Step 8:

[1281] The server generates appropriate product information and parenting advice based on the product location information in the store and the user data, and displays it on the smart glasses display. The input includes the user's location information and related data, and the output is the product information and parenting advice displayed on the smart glasses.

[1282] The above are the specific processing steps for carrying out the present invention, which make it easier for users to obtain information and advice on childcare in real time, and enable them to smoothly select childcare-related products in physical stores.

[1283] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1284] This invention is a system that provides optimal child-rearing advice by eliminating the anxieties and doubts that new fathers face in child-rearing. This system uses the user's device, a server, and an emotion engine to collect and analyze data and provide specific child-rearing advice in real time.

[1285] Collecting user information

[1286] The device collects various data related to the user's behavior and environment. Specifically, it periodically acquires calendar information, GPS data, and information on the apps used. The device also has an emotion engine that analyzes the user's voice and facial expressions to generate emotion data.

[1287] Specific examples

[1288] If a user has "Putting the child to bed (8:00 PM)" scheduled on their smartphone calendar, the device will detect this information. It will also use GPS data to confirm that the user is at home during that time. Furthermore, the emotion engine will analyze the user's tone of voice and facial expressions to determine whether the user is feeling stressed.

[1289] Data Transfer

[1290] The collected data is sent from the device to a server in real time, including calendar information, GPS data, app usage history, and emotional data.

[1291] Data storage and analysis

[1292] The server stores the received data in a database for each user. It also analyzes the user's behavioral patterns based on the accumulated data. The analysis is performed using an AI model, comparing past data with data from other users. Furthermore, emotional data is used to customize the content of advice.

[1293] Specific examples

[1294] The server analyzes specific behavioral patterns when putting the user to sleep based on data from the past week, and if the user is feeling stressed, it generates advice including relaxation techniques.

[1295] Generating Advice

[1296] The server generates parenting advice based on the results of the behavioral pattern analysis. The advice is provided in text, video, image, and other formats. Based on the emotional data, appropriate advice is added according to the user's emotional state.

[1297] Specific examples

[1298] The server generates advice including "5 effective ways to put a child to sleep," including the specific method of "gently patting the child's stomach." Furthermore, if the user is feeling stressed, it adds a relaxation technique such as "take a deep breath before putting the child to sleep."

[1299] Providing advice

[1300] The generated child-rearing advice is sent to the user's device at an appropriate time, and the device notifies the user of the received advice and displays it.

[1301] Specific examples

[1302] The server sends the generated advice to the device 15 minutes (19:45) before bedtime (20:00), and the device notifies the user. If the user's stress level is high, the device also provides relaxation advice taking that into account.

[1303] This system allows new fathers to receive specific child-rearing advice in real time based on their own behavior, environment, and emotional state, reducing the burden of child-rearing and supporting the harmonious development of the family.

[1304] The processing flow will be explained below.

[1305] Step 1:

[1306] Collecting device information

[1307] The user's device periodically collects calendar information, GPS data, and information about the apps they use. It also uses an emotion engine to analyze the user's voice and facial expressions to generate emotion data. This information is important for understanding the user's behavior and emotional state.

[1308] Specific examples

[1309] The device detects that "Putting the child to bed (20:00)" is registered on the user's calendar. GPS data confirms that the user is at home during that time. The emotion engine analyzes the user's tone of voice and facial expression and determines that the user's stress level is high.

[1310] Step 2:

[1311] Sending data

[1312] The device transmits the collected calendar information, GPS data, history of app usage, and emotion data to the server in real time.

[1313] Step 3:

[1314] Data storage

[1315] The server stores the received data in a database for each user, which is used for further analysis and advice generation.

[1316] Step 4:

[1317] Behavioral pattern analysis

[1318] The server analyzes the user's accumulated data, compares past data with that of other users, extracts the user's behavioral patterns, and makes predictions. Advanced analysis is performed using AI models.

[1319] Specific examples

[1320] The server analyzes calendar data from the past week to determine whether the user tends to put their child to bed at 8 p.m., and also uses emotional data to determine whether the user tends to feel stressed when putting their child to bed.

[1321] Step 5:

[1322] Generating Advice

[1323] The server generates parenting advice tailored to the user based on the analysis of the behavioral patterns and emotional data. The advice is customized according to the user's behavior and emotional state.

[1324] Specific examples

[1325] The server generates advice including "5 effective ways to put a child to sleep," including "gently patting the tummy" as one of the suggestions. Furthermore, considering that the user is feeling stressed, the server adds "taking deep breaths to calm the mind."

[1326] Step 6:

[1327] Sending Advice

[1328] The server transmits the generated child-rearing advice to the user's terminal at an appropriate time.

[1329] Step 7:

[1330] Advice Notification

[1331] The terminal notifies the user of the received advice and displays it, allowing the user to take action based on the advice.

[1332] Specific examples

[1333] The server sends the generated advice to the device 15 minutes before bedtime at 8:00 PM (7:45 PM). The device notifies the user of the advice and displays it. If the user is feeling stressed, the device also provides additional advice on relaxation techniques.

[1334] Through these steps, the system enables new fathers to receive optimal child-rearing advice and effectively resolves their anxieties and questions about child-rearing.

[1335] Example 2

[1336] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1337] To alleviate the anxieties and doubts that new fathers face in child-rearing and provide optimal child-rearing advice, it is necessary to understand the behavior and emotional state of each user and provide specific advice based on that in real time. However, conventional systems have difficulty generating advice that fully reflects each user's individual behavioral patterns and emotional state, resulting in the problem that the advice provided is general and not specific or effective.

[1338] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1339] In this invention, the server includes means for collecting calendar information, location data, and information on software used from the user's device, means for analyzing the collected data to grasp the user's emotional state, means for analyzing the user's behavioral patterns based on the data, means for generating child-rearing advice based on the analysis of the behavioral patterns and emotional state, and means for notifying the user's device of the child-rearing advice, thereby making it possible to provide specific and effective child-rearing advice based on the behavior and emotional state of each individual user in real time.

[1340] A "terminal" is an electronic device used by a user that has functions such as information collection, display, and communication.

[1341] "Calendar information" refers to data about events and schedules that a user has entered into a calendar application on the terminal.

[1342] "Location data" refers to information about a user's geographic location obtained by the user's device, and is collected via a GPS system or the like.

[1343] "Information about software used" is data related to the usage history and usage status of applications used by the user on the terminal.

[1344] "Emotional state" refers to the emotions and psychological state of a user, and is estimated using technologies such as voice analysis and facial expression recognition.

[1345] A "behavioral pattern" is a certain behavioral pattern or habit obtained as a result of analyzing a user's past behavior and behavioral tendencies.

[1346] "Childcare advice" is information such as specific instructions, suggestions, and advice regarding childcare, and is generated based on the user's behavioral patterns and emotional state.

[1347] A "server" is a computer system that communicates with terminals via a network, stores data, analyzes, processes data, and provides information.

[1348] "Means of collection" refers to the functions and processes for obtaining various data from the device (calendar information, location data, information on software used).

[1349] "Means of analysis" refers to the functions and processes for analyzing and processing the user's behavioral patterns and emotional state based on the collected data.

[1350] The "notification means" refers to a function or process for sending the generated child-rearing advice to the user's terminal and notifying the user.

[1351] This invention is a system that provides optimal child-rearing advice by eliminating the anxieties and doubts that new fathers face in child-rearing. This system utilizes the user's device, a server, and an emotion engine to collect and analyze data and provide specific child-rearing advice in real time.

[1352] Collecting user information

[1353] The user's device is equipped with hardware and software for collecting various data, including a calendar application, a GPS module, and software for monitoring the usage of various applications. It also includes an emotion engine for analyzing the user's voice and facial expressions.

[1354] As a concrete example of the "Mode for Carrying Out the Invention," consider a case where a user has entered "Putting the child to bed (20:00)" in their smartphone calendar. In this system, the device detects this information and simultaneously confirms via GPS data that the user is at home at that time. Furthermore, the emotion engine analyzes the user's tone of voice and facial expression to determine their stress level.

[1355] Data Transfer and Storage

[1356] The collected data is sent in real time from the user's device to a server, including calendar information, GPS data, app usage history, and emotional data.

[1357] The server stores the received data in a database for each user. The stored data is managed in a format linked to the user ID and is later used to analyze behavioral patterns.

[1358] Analyzing data and generating advice

[1359] The server uses an AI model based on the accumulated data to analyze the user's behavioral patterns. This analysis compares past data with other users' data to obtain highly accurate results. It also uses emotional data to understand the user's emotional state and customize the advice provided.

[1360] For example, the server analyzes specific behavioral patterns when putting a child to bed based on data from the past week, and if the user is experiencing high stress levels, generates advice including relaxation techniques.

[1361] The server generates parenting advice based on the analysis results. This advice is provided in text, image, video, and other formats. For example, advice can be generated that includes "five effective ways to put your child to sleep," including the specific method of "gently patting the child's tummy." Furthermore, if the user is feeling stressed, the server can add relaxation tips, such as "take a deep breath before putting the child to sleep."

[1362] Providing advice

[1363] The generated childcare advice is sent to the user's device at the appropriate time. The device notifies the user of the received advice and displays it. As a specific example, the server sends the generated advice to the device 15 minutes (19:45) before bedtime (20:00), and the device notifies the user. At this time, if the user's emotional data indicates a high stress level, the device will also notify the user of relaxation methods that take this into consideration.

[1364] This allows new fathers to receive specific child-rearing advice in real time that is tailored to their own behavior, environment, and emotional state, reducing the burden of child-rearing and supporting the harmonious development of their families.

[1365] (Example of a prompt)

[1366] "How do I help my baby relax while I'm getting him to sleep?"

[1367] "What are some easy ways to relax when you're stressed?"

[1368] "Please tell me the specific steps to make getting your child to sleep easier."

[1369] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1370] Step 1:

[1371] Collecting user information

[1372] The device collects calendar information, location data, and information about the software being used. Input data includes calendar information registered by the user on the device, location data obtained from the GPS module, and information about the applications being used. The device periodically obtains this data and temporarily stores the collected information. Specifically, it obtains schedule information from the calendar app, checks the user's current location from GPS data, and records the history of the applications being used.

[1373] Step 2:

[1374] Emotional state analysis

[1375] The device inputs the collected voice and facial expression data into an emotion engine, which outputs it as emotional data. The emotion engine uses voice analysis and facial recognition technology to analyze the user's emotional state. It receives voice data and facial expression images as input, and generates data representing stress levels and emotional states as output. Specifically, it analyzes voice recorded using a microphone and facial expressions captured with a camera.

[1376] Step 3:

[1377] Data Transfer

[1378] The device sends the collected calendar information, location data, information on the software used, and emotion data to the server. The input data is information stored in the device, and the output data is data packets sent to the server. Specifically, the device sends all collected data to the server at regular intervals.

[1379] Step 4:

[1380] Data storage

[1381] The server stores the received data in a database. Input data includes calendar information, location data, software used, and emotion data sent from the device, and the output is a database entry. Specifically, the server analyzes the received data, associates it with the user ID, and records it in the database.

[1382] Step 5:

[1383] Analysis of behavioral patterns and emotional states

[1384] The server analyzes the user's behavioral patterns and emotional state based on the received data. The input data includes past data and data from other users, and the output is the analysis results. Specifically, the server inputs the data into an AI model, which then analyzes the user's behavioral patterns and emotional state.

[1385] Step 6:

[1386] Generating Advice

[1387] The server generates parenting advice based on the results of analyzing behavioral patterns and emotional data. The input data are the results of behavioral pattern analysis and emotional state analysis, and the output is parenting advice. In concrete terms, the server uses the generative AI model to create parenting advice in text, image, and video format that is optimal for the user's condition.

[1388] Step 7:

[1389] Providing advice

[1390] The server sends the generated parenting advice to the user's device, which then notifies and displays it to the user. The generated parenting advice is input data, and the advice is displayed on the user's device as output. Specifically, the server sends the generated advice to the device at the appropriate time, and the device notifies the user via push notification, etc.

[1391] (Application example 2)

[1392] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1393] Today's new fathers often face many anxieties and questions about child-rearing. In particular, they lack advice tailored to their specific child-rearing situations and support that takes into account the father's own emotional state. This can increase stress and result in a decline in the quality of child-rearing. Because conventional systems do not provide customized advice based on emotional states and behavioral patterns, an effective solution to this problem is needed.

[1394] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting data from the user's terminal, means for analyzing the user's behavioral patterns based on the data, and means for customizing advice based on emotional data. This makes it possible to provide child-rearing advice that is suited to the user's specific behavioral patterns and emotional state.

[1395] "User's terminal" is a general term for a communication-enabled device used by a user, and mainly refers to a smartphone, smart glasses, a head-mounted display, or a robot.

[1396] "Data" refers to all information related to the user's behavior and environment, including calendar information, GPS data, information about the apps used, and emotional data generated from voice and facial expressions.

[1397] "Server" means a computer system on a network that receives and stores data, analyzes it, generates advice, and sends it to a user's device.

[1398] "Behavioral patterns" refer to specific behavioral patterns or tendencies derived from a user's past and present behavior.

[1399] "Emotion data" refers to information about the user's emotional state obtained by analyzing the user's voice and facial expressions.

[1400] "Parenting advice" refers to specific and practical guidance and suggestions regarding child-rearing that are generated based on the user's behavioral patterns and emotional state.

[1401] "Customization" refers to the process of tailoring advice content to a user's individual behavioral patterns and emotional state.

[1402] "Notification" refers to the act of sending childcare advice to the user's device in real time to inform the user.

[1403] This invention is a system that resolves the anxieties and doubts that new fathers face in child-rearing and provides optimal child-rearing advice in real time. The system consists of a user terminal, a server, and an emotion engine.

[1404] System configuration

[1405] User's device

[1406] The user's device is a communication-enabled device such as a smartphone, smart glasses, a head-mounted display, or a robot. The device collects the following data:

[1407] Calendar information: Get scheduled childcare activities and more.

[1408] GPS data: Obtaining the user's location.

[1409] App usage information: Obtain a history of apps used by the user.

[1410] Emotional data: The user's emotional state is obtained through analysis of voice and facial expressions.

[1411] Data collection and analysis

[1412] 1. Data Collection

[1413] The device periodically collects various data related to the user's behavior and environment. The emotion engine analyzes the user's voice and facial expressions to generate emotion data.

[1414] 2. Data Transfer

[1415] The collected data is sent to a server in real time.

[1416] Processing on the server

[1417] 1. Data storage and analysis

[1418] The server stores the received data in a database for each user. The stored data is used to analyze the user's behavioral patterns. The analysis is performed by comparing the data with past data and data from other users. The content of advice is also customized based on emotional data.

[1419] Hardware and software used

[1420] Hardware: Servers, databases, smartphones

[1421] Software: Python, API, TensorFlow, Django (or Flask), sentiment analysis engine

[1422] Generating and Serving Advice

[1423] 1. Advice Generation

[1424] The server generates parenting advice based on the analysis results. The advice is provided in text, video, image, and other formats. Based on the emotional data, the server customizes the advice to suit the user's emotional state.

[1425] 2. Advice Notice

[1426] The generated child-rearing advice is notified to the user's terminal in real time shortly before the time of the user's specific activity.

[1427] Specific examples

[1428] For example, if a user plans to put their child to bed at 8:00 PM, the device will collect that information and notify them of advice generated by the server at 7:45 PM. If the user's stress level is determined to be high, they will also be notified of relaxation techniques.

[1429] Prompt Sentence Examples

[1430] The user is in the following emotional state: Stress

[1431] Recent patterns of behavior include:

[1432] Calendar: Bedtime (20:00)

[1433] GPS Location: Home

[1434] App usage history: Parenting apps, relaxation apps

[1435] Generate specific parenting advice, including "5 effective ways to get your baby to sleep," to address any concerns or questions users may have. Also, provide relaxation advice if users are feeling stressed.

[1436] This invention allows new fathers to receive specific child-rearing advice in real time that is tailored to their own behavior, environment, and emotional state, reducing the burden of child-rearing and supporting the harmonious development of the family.

[1437] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1438] Step 1:

[1439] The device collects data related to the user's behavior and environment. Specifically, it acquires calendar information, GPS data, information on the apps used, and emotional data generated from voice and facial expressions. The input data is the user's calendar information, GPS location information, app usage history, voice data, and video data, and the output data is a set of collected data including this information.

[1440] Step 2:

[1441] The terminal transmits the collected data to the server in real time. The input data is the data collected in step 1, and the output data is the data transmitted to the server. The specific transmission operation uses a communication protocol such as an HTTP request or WebSocket.

[1442] Step 3:

[1443] The server stores the received data in a database. The input data is the data sent from the terminal, and the output data is the stored database entry. Specifically, it executes an INSERT statement against the database (e.g., MySQL or PostgreSQL).

[1444] Step 4:

[1445] The server analyzes the user's behavioral patterns based on the stored data. The input data is past data stored in the database and data from other users, and the output data is the analysis results of the behavioral patterns. Specifically, the data is analyzed using a machine learning model (e.g., TensorFlow or PyTorch).

[1446] Step 5:

[1447] The server generates advice based on the user's emotional data. The input data are the analysis results of behavioral patterns and emotional data, and the output data is the generated parenting advice. Specifically, the system uses an emotion analysis engine to generate prompt sentences, which are then input into the AI ​​model to obtain advice.

[1448] Step 6:

[1449] The server notifies the user's device of the generated parenting advice. The input data is the generated advice, and the output data is the notification sent to the device. Specifically, the advice is sent to the device using a push notification service (e.g., Firebase Cloud Messaging).

[1450] Users can receive real-time advice based on specific activity times, which can improve the quality of their child-rearing. This series of processing steps realizes a system that effectively solves many of the challenges new fathers face in child-rearing.

[1451] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1452] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1453] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1454] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1455] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1456] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1457] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1458] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1459] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1460] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1461] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1462] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1463] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1464] 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.

[1465] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1466] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1467] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1468] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1469] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1470] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1471] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1472] The following is further disclosed regarding the above embodiment.

[1473] (Claim 1)

[1474] means for collecting data from a user's terminal;

[1475] means for transmitting said data to a server;

[1476] means for analyzing user behavior patterns based on the data;

[1477] means for generating child-rearing advice based on the behavioral pattern analysis;

[1478] means for notifying the user of the child-rearing advice;

[1479] A system including:

[1480] (Claim 2)

[1481] 2. The system according to claim 1, further comprising means for analyzing the user's behavioral patterns by comparing them with past data and data of other users.

[1482] (Claim 3)

[1483] 2. The system of claim 1, wherein the user's terminal includes means for collecting calendar information, GPS data, and information on used apps.

[1484] "Example 1"

[1485] (Claim 1)

[1486] means for collecting calendar information, location information, and application usage history from a user's device;

[1487] means for transmitting the collected data to a server in real time;

[1488] means for storing the data received by the server in a database for each user;

[1489] means for using a generative AI model to analyze user behavior patterns based on the stored data;

[1490] means for generating child-rearing advice based on the analysis results;

[1491] means for notifying the generated childcare advice to the user's device at an appropriate time;

[1492] A system including:

[1493] (Claim 2)

[1494] 2. The system according to claim 1, wherein the server further comprises means for analyzing the user's behavioral patterns by comparing them with past data and data of other users.

[1495] (Claim 3)

[1496] 2. The system according to claim 1, wherein the user's terminal includes means for collecting the collected calendar information, location information, and application usage history into packets and transmitting the packets to a server.

[1497] "Application Example 1"

[1498] (Claim 1)

[1499] means for collecting data from a user's terminal;

[1500] means for transmitting said data to a server;

[1501] means for analyzing user behavior patterns based on the data;

[1502] means for generating child-rearing advice based on the behavioral pattern analysis;

[1503] means for notifying the user of the child-rearing advice;

[1504] a means for displaying parenting advice and product information in a store using smart glasses;

[1505] A system including:

[1506] (Claim 2)

[1507] 2. The system according to claim 1, further comprising means for analyzing the user's behavioral patterns by comparing them with past data and data of other users.

[1508] (Claim 3)

[1509] 2. The system of claim 1, wherein the user's terminal includes means for collecting calendar information, GPS data, and information on used apps.

[1510] "Example 2: Combining Emotion Engines"

[1511] (Claim 1)

[1512] means for collecting calendar information, location data, and software usage information from a user's terminal;

[1513] means for analyzing the collected data to grasp the emotional state of the user;

[1514] means for transmitting said data to a server;

[1515] means for analyzing user behavior patterns based on the data;

[1516] means for generating parenting advice based on the analysis of said behavioral patterns and emotional states;

[1517] means for notifying the user of the child-rearing advice;

[1518] A system including:

[1519] (Claim 2)

[1520] 2. The system according to claim 1, further comprising means for analyzing the user's behavioral patterns by comparing them with past data and data of other users.

[1521] (Claim 3)

[1522] 10. The system of claim 1, wherein the user's terminal includes means for collecting calendar information, location data, and software usage information.

[1523] "Application example 2 when combining emotion engines"

[1524] (Claim 1)

[1525] means for collecting data from a user's terminal;

[1526] means for transmitting said data to a server;

[1527] means for analyzing user behavior patterns based on the data;

[1528] means for generating child-rearing advice based on the behavioral pattern analysis;

[1529] means for notifying the user of the child-rearing advice;

[1530] A means for generating emotion data;

[1531] A means to customize advice based on emotional data;

[1532] A system including:

[1533] (Claim 2)

[1534] 2. The system according to claim 1, further comprising means for analyzing the user's behavioral patterns by comparing them with past data and data of other users.

[1535] (Claim 3)

[1536] 2. The system of claim 1, wherein the user's terminal includes means for collecting calendar information, GPS data, and information on used apps. [Explanation of symbols]

[1537] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for collecting data from a user's terminal; means for transmitting said data to a server; means for analyzing user behavior patterns based on the data; means for generating child-rearing advice based on the behavioral pattern analysis; means for notifying the user of the child-rearing advice; A system including:

2. The system according to claim 1 , further comprising means for analyzing the user's behavioral patterns by comparing them with past data and data of other users.

3. The system of claim 1 , wherein the user's terminal includes means for collecting calendar information, GPS data, and information on used apps.

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