System

Abstract

To provide a support system for pregnancy, childbirth, and childcare, allowing a user to receive individually suitable latest information and advice, and to obtain mental support.SOLUTION: The system includes means for collecting user data, means for generating information on pregnancy, childbirth, and child-raising based on the collected data, means for distributing the generated information to the user, means for generating and providing personalized advice based on a question of the user, means for managing, analyzing, and monitoring health data of a mother and a child, means for performing a stress check for supporting mental health of the user, analyzing the stress check, and proposing an appropriate relaxation method, means for recommending a community and allowing users to share information, and means for analyzing uploaded photographs and selecting an appropriate photograph to generate an album.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] Pregnancy, childbirth, and child-rearing are life stages in which individually tailored information and support are essential. However, in today's information-overloaded world, it can be difficult for users to identify information that is appropriate for them, and as a result, there is a risk that they may become dependent on inappropriate information. Furthermore, the pregnancy and child-rearing process often causes anxiety and stress, and methods to alleviate this mental burden are needed. Furthermore, there are a lack of opportunities to communicate with people in the same situation and share information and experiences. [Means for solving the problem]

[0005] In order to solve these problems, the present invention provides a pregnancy, childbirth, and child-rearing support system that incorporates the following means: a means for collecting user data, a means for generating information related to pregnancy, childbirth, and child-rearing based on the collected data, a means for distributing the generated information to users, a means for generating and providing personalized advice based on user questions, a means for managing, analyzing, and monitoring health data of mothers and children, a means for conducting and analyzing stress checks to support the user's mental health and suggesting appropriate relaxation methods, a means for recommending communities and allowing users to share information with each other, and a means for analyzing uploaded photos, selecting appropriate photos, and generating albums. This allows users to receive the latest information and advice that is individually tailored to them, and also provides psychological support.

[0006] "User data" refers to personal information, health information, questions, etc. that users provide to the system.

[0007] "Means of generating information" refers to the methods and technologies that enable AI to generate up-to-date information on pregnancy, childbirth, and child-rearing based on collected data.

[0008] "Means for delivering to users" refers to methods and techniques for delivering the generated information and advice to user terminals.

[0009] "Personalized advice" refers to advice or information that is optimized based on a user's individual profile information and questions.

[0010] "Health data management tools" refers to methods and technologies for recording, storing and updating data on the health status of mothers and children.

[0011] "Means of analysis and monitoring" refers to the methods and technologies that enable AI to analyze collected health data and provide users with feedback and warnings appropriate to the situation.

[0012] "Means for conducting stress checks" refers to methods and techniques for conducting questionnaires and tests to assess the mental health of users.

[0013] The "means for suggesting relaxation methods" refers to methods and technologies for suggesting appropriate relaxation techniques and activities to users based on the results of the stress check.

[0014] "Means for recommending communities" refers to methods and technologies for recommending appropriate online communities based on a user's profile information and promoting participation.

[0015] "Means for sharing information" refers to interfaces and technologies that allow users to exchange and share information and experiences within a community.

[0016] "Means for analyzing photos" refers to methods and technologies in which AI analyzes uploaded photo data and selects important photos based on facial recognition technology.

[0017] "Means for generating an album" refers to methods and techniques for automatically generating a digital album using selected photos. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

[0026] [First embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0039] This invention is a system that provides a series of information and support related to pregnancy, childbirth, and child-rearing, and its core is information generation and personalization using AI technology. The components of this system consist of various means for collecting user data and providing information and advice generated based on that data.

[0040] Overview of program processing

[0041] 1. How we collect user data

[0042] Users first enter their profile information into the device, including their age, number of weeks pregnant, health status, and past medical history.

[0043] The terminal sends this information to the server, which stores it in a database.

[0044] 2. Information generation means

[0045] The server periodically collects data from external medical databases and the latest research papers and stores it in an internal database.

[0046] The AI ​​uses the collected data to generate up-to-date information on pregnancy, childbirth, and parenting, which is then presented through an interface for users to access.

[0047] 3. Information distribution methods

[0048] The server sends the generated information to the device for viewing by the user, who can access this information through an app or web interface.

[0049] 4. Means of personalized advice delivery

[0050] A user enters a specific question into the terminal, which then transmits the question to the server.

[0051] The server uses AI to generate personalized advice based on the user's profile information and questions, and sends the answer to the device.

[0052] Examples:

[0053] When a user asks, "What can I do to combat morning sickness?", the AI ​​will refer to other data that matches the user's profile (for example, the number of weeks pregnant) and provide specific measures, such as "Diets containing ginger are effective."

[0054] 5. Health data management and monitoring measures

[0055] Users enter their own and their children's health information (weight, body temperature, dietary details, etc.) into the device.

[0056] The device sends this data to a server, which then uses AI to analyze the data and monitor the user's health.

[0057] Examples:

[0058] Users enter their daily weight, and the server analyzes the data and sends alerts if their weight is increasing too rapidly.

[0059] 6. Mental health support measures

[0060] The server periodically sends a stress check questionnaire to the user's device and collects the results.

[0061] The AI ​​will analyze the survey responses and suggest relaxation and stress reduction methods as needed.

[0062] Examples:

[0063] If the user answers the questionnaire indicating high stress, the server will suggest "relaxation breathing techniques."

[0064] 7. Community Recommendations

[0065] The server recommends appropriate online communities based on the user's profile.

[0066] Users can join recommended communities and share information and experiences with other members.

[0067] Examples:

[0068] New moms are encouraged to join the "First Time Parenting Community" where they can share information and experiences with other new moms.

[0069] 8. Photo analysis and album generation method

[0070] Users upload ultrasound images and photos of their child's growth record to the device.

[0071] The server uses facial recognition technology to analyze the photos and select the most important ones.

[0072] A digital album is automatically generated based on the selected photos.

[0073] Examples:

[0074] When users upload one ultrasound photo per month, the server organizes them in chronological order and creates a growth record album.

[0075] Through the above components and processes, this system comprehensively provides the information and support needed at each stage of pregnancy, childbirth, and child-rearing. This allows each user to not only obtain the information that is most suitable for them, but also receive psychological support. Furthermore, by sharing information with other users in the same situation through the community function, users can receive even more comprehensive support.

[0076] The processing flow will be explained below.

[0077] 1. Generating information about pregnancy, childbirth, and child-rearing

[0078] Step 1:

[0079] The server periodically collects data from external medical databases and the latest research papers.

[0080] Specific operation: The server retrieves information from medical journals and other medical sources through APIs and stores it in an internal database.

[0081] Step 2:

[0082] The server inputs the collected data into AI to generate information about pregnancy, childbirth, and child-rearing.

[0083] Specific operation: The AI ​​analyzes the collected data and uses a natural language generation algorithm to create sentences that are easy for users to understand.

[0084] Step 3:

[0085] The server distributes the generated information through a user interface (app or website).

[0086] Specific operation: The generated articles and information pages are uploaded to a web server so that users can access them.

[0087] 2. Providing personalized advice to users

[0088] Step 1:

[0089] Users enter their profile information into the device (e.g., age, number of weeks pregnant, health status).

[0090] Specific operation: The device displays a profile entry form and, once completed, sends the data to the server.

[0091] Step 2:

[0092] The user inputs a specific question into the terminal.

[0093] Specific operation: The terminal displays a question form, and when the user enters a question and presses the send button, the question data is sent to the server.

[0094] Step 3:

[0095] The server inputs the user's profile information and questions into the AI ​​to generate personalized advice.

[0096] What it does: The AI ​​searches the database and creates personalized advice based on relevant information.

[0097] Step 4:

[0098] The server transmits the generated advice to the user terminal.

[0099] Specific operation: The created answer is delivered to the device in real time.

[0100] 3. Health care for mothers and children

[0101] Step 1:

[0102] Users input their daily health data (weight, body temperature, dietary content, etc.) into the device.

[0103] Specific operation: The terminal provides an input interface, and after data is entered, pressing the send button sends the data to the server.

[0104] Step 2:

[0105] The terminal transmits the input data to the server.

[0106] Specific operation: The device sends data to the server via an HTTP request or API.

[0107] Step 3:

[0108] The server analyzes the received data using AI and monitors the health status.

[0109] What it does: The AI ​​analyzes the data, checks for any anomalies, and runs algorithms to assess whether it's within the normal range.

[0110] Step 4:

[0111] The server generates feedback for the user based on the analysis results and sends it to the device.

[0112] Specific operation: Analysis results and recommended actions are sent to the device in real time.

[0113] 4. Mental health support

[0114] Step 1:

[0115] The server periodically sends a stress check questionnaire to the terminal.

[0116] Specific operation: The server generates a stress check form and sends it to the terminal on the specified schedule.

[0117] Step 2:

[0118] The user answers the questionnaire and enters it into the terminal.

[0119] Specific operation: The terminal provides an interface for answering the survey questions and displays a button to submit the answers.

[0120] Step 3:

[0121] The terminal sends the questionnaire responses to the server.

[0122] Specific operation: Survey response data is sent to the server via HTTP request or API.

[0123] Step 4:

[0124] The server analyzes the response data using AI and evaluates stress levels.

[0125] What it does: The AI ​​analyzes your answers and runs an algorithm to quantify your stress level.

[0126] Step 5:

[0127] Based on the analysis results, the server suggests relaxation methods and sends them to the device.

[0128] Specific operation: Generate proposal content and send it to the terminal.

[0129] 5. Community Recommendations

[0130] Step 1:

[0131] The server recommends appropriate communities based on the user's profile.

[0132] Specific Operation: The server parses the profile information and generates a list of appropriate communities.

[0133] Step 2:

[0134] Users join recommended communities.

[0135] Specific operation: The terminal provides a participation interface and displays a participation button.

[0136] Step 3:

[0137] Users share information and experiences within the community.

[0138] Specific operation: The device provides messaging and posting functions to share information with other users.

[0139] 6. Memories storage

[0140] Step 1:

[0141] Users upload ultrasound images and photos of their child's growth record to the device.

[0142] Specific operation: The terminal provides a photo upload interface and sends the uploaded photos to the server.

[0143] Step 2:

[0144] The server analyzes the uploaded photos using facial recognition technology.

[0145] How it works: The AI ​​analyzes the photo data and runs an algorithm to identify important people in the photos.

[0146] Step 3:

[0147] The server selects important photos and generates an automatic album.

[0148] Specific operation: Organize photos chronologically and generate a digital album layout for the user.

[0149] Step 4:

[0150] The server transmits the generated album to the terminal.

[0151] Specific Actions: Create a digital album and provide a link for users to access it.

[0152] Example 1

[0153] 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."

[0154] Conventional information systems related to pregnancy, childbirth, and child-rearing only provide general information, making it difficult for individual users to obtain information and advice that is optimized for them. Furthermore, centralized management of health data and mental health support were insufficient, making it impossible to provide the comprehensive support that users need.

[0155] 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.

[0156] In this invention, the server includes a means for collecting user data, a means for generating information about pregnancy, childbirth, and child-rearing based on the collected data, and a means for distributing the generated information to the user. This enables personalized information and support. The system also includes a means for generating and providing personalized advice based on the user's questions, a means for managing, analyzing, and monitoring health data, a means for conducting and analyzing stress checks to support the user's mental health, and suggesting appropriate relaxation methods, a means for recommending online communities and allowing users to share information, and a means for analyzing uploaded images, selecting appropriate images, and generating a digital album. This allows users to receive comprehensive, personalized support, providing multifaceted support such as health management, mental health care, and promoting information sharing.

[0157] "User data" refers to data including profile information, health information, questions, etc. entered by the user.

[0158] "Information generation" is the process of generating information about pregnancy, childbirth, and parenting based on collected data.

[0159] "Information distribution" is the process of sending the generated information to the user's terminal and making it viewable.

[0160] "Personalized advice" is specific advice that is generated based on a user's individual questions and profile information.

[0161] "Health data management" is the process of collecting, analyzing, and monitoring user and child health information.

[0162] "Mental health support" is the process of conducting stress checks, analyzing stress levels, and suggesting appropriate relaxation methods to support the mental health of users.

[0163] "Online community recommendation" is the process of recommending appropriate communities based on a user's profile and encouraging them to join.

[0164] "Digital album generation" is the process of analyzing uploaded images, selecting important images, and creating a digital album.

[0165] "External data collection" is the process of obtaining data from external medical databases and research materials and storing it in an internal database.

[0166] "Personalized advice" refers to customized advice generated based on a user's profile information, health status, pregnancy stage, and health concerns.

[0167] MODE FOR CARRYING OUT THE INVENTION

[0168] This invention is a comprehensive system for providing information and support related to pregnancy, childbirth, and child-rearing, and utilizes AI technology to provide users with personalized information and advice. The purpose of this invention is to help users obtain the information they need in a timely and appropriate manner at each stage of their pregnancy and child-rearing lives.

[0169] 1. Collection of User Data

[0170] Users enter profile information such as age, number of weeks pregnant, health status, and past medical history into a device, which can be a smartphone, tablet, or PC.

[0171] The device sends the collected information to a server using a secure communication protocol (e.g., HTTPS).

[0172] The server validates the received data and stores it in a database, which can be an SQL database or a NoSQL database.

[0173] 2. Information Generation

[0174] The server periodically collects information from external medical databases (e.g., PubMed) and the latest research materials and stores them in an internal database.

[0175] AI models (e.g., GPT-3) analyze collected medical data and generate up-to-date information, including articles and advice on pregnancy, childbirth, and parenting.

[0176] 3. Information distribution

[0177] The server distributes the generated information to users, and in this process, the most appropriate information is selected based on each user's profile.

[0178] Users can access the information through an application or a web interface.

[0179] 4. Providing personalized advice

[0180] The user enters a specific question into the terminal and sends the question to the server.

[0181] The server uses AI to generate personalized advice based on the user's profile information and questions, and sends the answer to the device.

[0182] Example: When a user asks, "What can I do to prevent morning sickness?", the AI ​​will provide specific advice based on the user's number of weeks pregnant, such as "Diets that include ginger are effective."

[0183] 5. Health data management and monitoring

[0184] Users enter their daily health information (e.g., weight, body temperature, dietary details) into the device.

[0185] The terminal transmits this health information to the server.

[0186] The server uses AI to analyze the data and sends an alert if there is an abnormality.

[0187] Example: When a user enters their daily weight, the AI ​​analyzes changes in weight and, if there is a sudden increase, sends a warning to "consult a doctor."

[0188] 6. Mental health support

[0189] The server periodically sends a stress check questionnaire to the user's terminal.

[0190] The user answers the questionnaire and the results are sent to the server.

[0191] The AI ​​model will analyze the survey results and suggest relaxation and stress reduction methods as needed.

[0192] Example: If a user answers in a way that indicates high stress, the AI ​​will suggest "breathing techniques for relaxation."

[0193] 7. Community Recommendations

[0194] The server recommends appropriate online communities based on the user's profile.

[0195] Users join recommended communities and share information and experiences with other members.

[0196] Example: A new mother is recommended a "first-time parenting community."

[0197] 8. Photo analysis and album generation

[0198] Users upload ultrasound images and photos of their child's growth record to the device.

[0199] The server uses facial recognition technology to analyze the uploaded photos and select important ones.

[0200] The server generates a digital album based on the selected photos.

[0201] Example: When a user uploads one ultrasound photo per month, AI analyzes it, organizes it chronologically, and creates a digital album.

[0202] Through these components and processes, the system provides users with personalized information and support, enabling them to achieve the comprehensive support they need at each stage of pregnancy, childbirth, and child-rearing life.

[0203] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0204] Processing flow

[0205] Step 1: Enter user data

[0206] Users fill out a form in the application with profile information such as age, pregnancy stage, health status, and past medical history.

[0207] Input: Age, gestational age, health status, medical history

[0208] Output: Data entered by the user

[0209] Specific behavior: The user enters information into an input field and presses the "Submit" button.

[0210] Step 2: Send user data

[0211] The terminal transmits the input user information to the server.

[0212] Input: Data entered by the user

[0213] Output: Data sent to the server

[0214] Specific operation: The device sends data to the server using the HTTPS protocol.

[0215] Step 3: Save user data

[0216] The server validates the received user information and stores it in the database.

[0217] Input: Submitted user data

[0218] Output: Data stored in the database

[0219] What happens: The server checks the format and validity of the data and inserts it into the database.

[0220] Step 4: Gather external data

[0221] The server collects external medical databases and the latest research materials via API and stores them in an internal database.

[0222] Input: External databases and research materials

[0223] Output: Medical information stored in an internal database

[0224] Specific operation: The server periodically calls the API to collect new data and store it in the database.

[0225] Step 5: Information Generation

[0226] The AI ​​model generates up-to-date information on pregnancy, childbirth, and parenting based on collected medical data and user profiles.

[0227] Input: Medical information stored in an internal database, user profile

[0228] Output: Information provided to the user

[0229] What it does: AI models process data and generate reports and recommendations.

[0230] Step 6: Information distribution

[0231] The server transmits the generated information to the user's terminal.

[0232] Input: Information generated by the AI ​​model

[0233] Output: Information sent to the terminal

[0234] What it does: The server sends a notification to the user's device, making the information available in an app or web interface.

[0235] Step 7: Enter a specific question

[0236] The user enters a specific question into the terminal, which then transmits the question to the server.

[0237] Input: User's specific question

[0238] Output: The question sent to the server

[0239] Specific behavior: The user enters a question in the text box and presses the "Submit" button.

[0240] Step 8: Personalized advice generation

[0241] The server uses AI to generate personalized advice based on the user's questions and profile information and sends it to the device.

[0242] Input: User questions, profile information

[0243] Output: Personalized advice

[0244] What it does: The AI ​​model processes the data, generates specific advice, and sends it to the device.

[0245] Step 9: Enter and submit your health data

[0246] Users enter their daily health information into a terminal, which then transmits it to a server.

[0247] Input: Health information (weight, body temperature, dietary details, etc.)

[0248] Output: Health data sent to the server

[0249] Specific operation: The user enters health information in the app according to the format and presses the "Submit" button.

[0250] Step 10: Analyzing and monitoring health data

[0251] The server uses AI to analyze health data and sends an alert if there are any abnormalities.

[0252] Input: Collected health data

[0253] Output: Analysis results, warnings if necessary

[0254] What it does: The AI ​​model analyzes the data, detects abnormal patterns, generates alerts, and notifies the user.

[0255] Step 11: Mental Health Check

[0256] The server periodically sends a stress check questionnaire to the user, who then answers it.

[0257] Input: Stress check questionnaire response

[0258] Output: Analysis of survey results

[0259] Specific operation: The server sends a survey, the user answers, and the server receives and analyzes the answers.

[0260] Step 12: Suggested relaxation techniques

[0261] The AI ​​model analyzes the results of the stress check and suggests appropriate relaxation methods.

[0262] Input: Analysis results of stress check questionnaire

[0263] Output: Relaxation suggestions

[0264] Specific operation: The AI ​​model analyzes the data, generates the optimal relaxation method for the user, and notifies the device.

[0265] Step 13: Online Community Recommendations

[0266] The server recommends appropriate online communities based on the user's profile.

[0267] Input: User profile information

[0268] Output: Recommended community information

[0269] Specific operation: The server processes the data, selects the most suitable community for the user, and notifies them.

[0270] Step 14: Upload and analyze photos

[0271] Users upload ultrasound images and photos of their child's growth record to the device.

[0272] Input: Uploaded image

[0273] Output: Image data stored on the server

[0274] Specific behavior: The user selects a photo and presses the "Upload" button.

[0275] Step 15: Generate a digital album

[0276] The server uses facial recognition technology to analyze the images, select important images, and generate a digital album.

[0277] Input: Uploaded image data

[0278] Output: Generated digital album

[0279] Specific operation: The AI ​​model analyzes images and automatically generates an album to provide to the user.

[0280] Through these processing steps, the system provides users with personalized information and services, providing comprehensive support at each stage of pregnancy, childbirth, and child-rearing.

[0281] (Application example 1)

[0282] 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."

[0283] Previous information systems related to pregnancy, childbirth, and child-rearing were not able to assist users when selecting products in stores. This made it difficult for expectant mothers and parents to select the appropriate products they needed, and also increased the time and burden it took to search for products in stores. Furthermore, the lack of personalized product recommendations and optimal in-store routing based on individual users' profile information and health status meant that they were unable to provide an efficient and comfortable shopping experience.

[0284] 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.

[0285] In this invention, the server includes: means for collecting user data; means for generating information about pregnancy, childbirth, and child-rearing based on the collected data; means for distributing the generated information to users; means for generating and providing personalized advice based on user questions; means for managing, analyzing, and monitoring maternal and child health data; means for conducting and analyzing stress checks to support users' mental health and suggesting appropriate relaxation methods; means for recommending communities and allowing users to share information; means for analyzing uploaded photos, selecting appropriate photos, and creating albums; and means for recommending appropriate products and suggesting optimal in-store routing based on user profile information. This enables the provision of information and support tailored to the needs of individual users. It also makes it possible to streamline product searches in stores, providing a more comfortable and stress-free shopping experience.

[0286] "User Data" includes information about the user, such as profile information, health status, medical history, pregnancy weeks, and child ages.

[0287] "Information on pregnancy, childbirth, and child-rearing" refers to information related to health care, nutrition, child-rearing techniques, medical services, etc. for mothers and their children during pregnancy and after birth.

[0288] "Personalized advice" refers to providing customized advice tailored to a user's specific needs and circumstances based on their individual profile information and health status.

[0289] "Health data" refers to health-related information such as the weight, temperature, dietary habits, and medical records of the mother and child.

[0290] A "stress check" is a method of conducting a questionnaire or test to evaluate a user's mental state and analyzing the results.

[0291] "Relaxation methods" refer to specific techniques for reducing stress and achieving mental stability, such as breathing exercises and meditation.

[0292] A "community" refers to an online platform where users with similar circumstances can share information and experiences.

[0293] "Photo analysis" refers to the technology of analyzing image data uploaded by users and classifying or evaluating its content.

[0294] "Album generation" is the process of creating an automatically organized digital or physical photo album based on the analyzed photos.

[0295] "Product recommendation" is a means of selecting and suggesting products suitable for pregnancy and child-rearing based on the user's profile information.

[0296] "Routing" refers to providing optimal routes to help users efficiently find the desired product within a store.

[0297] This invention is a system that provides information and support related to pregnancy, childbirth, and child-rearing. This system collects user data and uses that data to generate information, provide advice, recommend products, and navigate within stores. Specific embodiments for implementing this system are described below.

[0298] 1. Collection of User Data

[0299] Using a device (such as a smartphone), the user enters their profile information, including age, number of weeks pregnant, health status, past medical history, and age of children. The device collects this information and sends it to a server, which stores the received data in a database.

[0300] 2. Information generation

[0301] The server periodically collects data from external medical databases and research papers and stores it in an internal database. Using AI technology, the server generates up-to-date information on pregnancy, childbirth, and parenting, and provides it through an interface for users to access. This AI technology includes, for example, generative AI models that utilize natural language processing (NLP).

[0302] 3. Information distribution

[0303] The generated information is sent from the server to the user's terminal, where the user can access the information through an application or web interface.

[0304] 4. Providing personalized advice

[0305] When a user types a specific question into the device, the question is sent to the server, where the AI ​​generates personalized advice based on the user's profile information and the question, and sends the answer back to the device.

[0306] 5. Health data management and monitoring

[0307] Users enter their own and their children's health information (weight, body temperature, dietary details, etc.) into the device. The device then sends this data to a server, which uses AI to analyze the data and monitor the health status. If any abnormalities, such as sudden weight gain, are detected, the server will send a warning to the user.

[0308] 6. Mental health support

[0309] The server periodically sends a stress check questionnaire to the user's device and collects the results. The AI ​​analyzes the questionnaire responses and suggests relaxation methods and stress reduction measures as needed.

[0310] 7. Community Recommendations

[0311] The server recommends suitable online communities based on the user's profile, and the user can join the recommended communities and share information and experiences with other members.

[0312] 8. Photo analysis and album generation

[0313] Users upload ultrasound images and photos of their child's growth record to their device, and the server uses facial recognition technology to analyze the images, selects important photos, and automatically creates a digital album.

[0314] 9. Product Recommendations and In-Store Navigation

[0315] Based on the user's profile information, the app recommends appropriate products, such as nutritional supplements and toys suited to the developmental stage of a child or expectant mother. It also displays the location of the recommended products in the store and provides the shortest route, allowing users to find the products efficiently.

[0316] Hardware and software used

[0317] Hardware: Smartphone

[0318] Software: Python, React Native as frontend, MySQL as database

[0319] AI Technology: Generative AI Models that Use Natural Language Processing (NLP)

[0320] Specific examples

[0321] Let's say a user is 20 weeks pregnant and shopping in a brick-and-mortar store. The user opens the in-store app on their smartphone.

[0322] 1. Collection of User Data

[0323] The user enters profile information (age, number of weeks pregnant, health status, etc.) and submits it.

[0324] 2. Providing personalized advice

[0325] When a user asks, "What can I do to combat morning sickness?", the AI ​​will provide personalized advice such as, "Diets containing ginger are effective."

[0326] 3. Health data management and monitoring

[0327] When a user enters their weight, if it is determined that their weight is increasing rapidly, the server will send a warning.

[0328] 4. Product Recommendations and In-Store Navigation

[0329] The system suggests recommended products such as folic acid supplements (A3) and vitamin D supplements (A5) and displays the shortest route within the store.

[0330] Prompt Sentence Examples

[0331] "For a user who is 20 weeks pregnant, please recommend the best products to purchase in a physical store and suggest a route, including specific shelf locations."

[0332] This allows users to shop comfortably and efficiently, while also providing support tailored to individual needs.

[0333] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0334] Step 1:

[0335] User Data Collection:

[0336] The user enters their profile information (age, number of weeks pregnant, health condition, past medical history, age of child, etc.) into the terminal. This input data is sent from the terminal to the server, and the server stores the received data in a database. The input here is the user's profile information, and the output is the user data stored on the server.

[0337] Step 2:

[0338] Information generation:

[0339] The server periodically collects data from external medical databases and research papers and stores it in an internal database. It uses AI technology (generative AI models) to generate up-to-date information on pregnancy, childbirth, and parenting. The input is external medical data and research papers, and the output is the generated up-to-date information.

[0340] Step 3:

[0341] Information distribution:

[0342] The server sends the generated information to the user's device, where the user can view the information through an application or web interface. The input is the generated information, and the output is the delivery of the information to the user's device.

[0343] Step 4:

[0344] Personalized advice provided:

[0345] When a user enters a specific question into the device, the question is sent to the server, where the AI ​​generates personalized advice based on the user's profile information and the question, and sends the answer to the device. The input is the user's question and profile information, and the output is personalized advice.

[0346] Step 5:

[0347] Health data management and monitoring:

[0348] Users enter their own and their children's health information (weight, body temperature, dietary details, etc.) into the device. The device sends this data to a server, which uses AI to analyze the data and monitor the health status. If any abnormalities are detected as a result of this analysis, a warning is sent. The input is the user's health data, and the output is the analysis results and a warning in the event of an abnormality.

[0349] Step 6:

[0350] Mental health support:

[0351] The server periodically sends a stress check questionnaire to the user's device and collects the results. The AI ​​analyzes the questionnaire responses and suggests relaxation methods and stress reduction measures as needed. The input is the questionnaire response data, and the output is the analysis results and suggested relaxation methods.

[0352] Step 7:

[0353] Community Recommendations:

[0354] The server recommends appropriate online communities based on the user's profile information. The user can join the recommended communities and share information and experiences with other members. The input is the user's profile information, and the output is the recommended community information.

[0355] Step 8:

[0356] Photo analysis and album generation:

[0357] Users upload ultrasound images and photos recording their child's growth to their device. The server analyzes the images using facial recognition technology and selects important photos. A digital album is automatically generated based on the selected photos. The input is the photo data uploaded by the user, and the output is the analysis results and the generated digital album.

[0358] Step 9:

[0359] Product recommendations and in-store navigation:

[0360] The server recommends appropriate products based on the user's profile information. The location information of the recommended products is compared with the store map to calculate the optimal route. The user can check the recommended products and their locations, as well as the shortest route within the store, through their device. The input is the user's profile information, store map information, and product data, and the output is recommended product information and the store route.

[0361] 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.

[0362] This invention combines an emotion engine with a comprehensive support system for pregnancy, childbirth, and child-rearing to recognize the user's emotions and provide more accurate, personalized support. The system uses AI technology to collect user data and provides personalized information and advice based on that data. In particular, the invention aims to utilize the user's emotion data to more accurately understand the user's mental health and overall well-being and provide appropriate support tailored to the user's needs.

[0363] Overview of program processing

[0364] 1. How we collect user data

[0365] Users enter their profile information into the device, including their age, pregnancy status, health status, and past medical history.

[0366] The terminal sends this information to the server, which stores it in a database.

[0367] 2. Information generation means

[0368] The server periodically collects data from external medical databases and the latest research papers and stores it in an internal database.

[0369] The AI ​​uses the collected data to generate up-to-date information on pregnancy, childbirth, and parenting, which is then presented through an interface for users to access.

[0370] 3. Information distribution methods

[0371] The server distributes the generated information through a user interface (app or website).

[0372] Users can access this information through an app or web interface.

[0373] 4. Means of personalized advice delivery

[0374] A user enters a specific question into the terminal, which then transmits the question to the server.

[0375] The server uses AI to generate personalized advice based on the user's profile information and questions, and sends the answer to the device.

[0376] Examples:

[0377] When a user asks, "What can I do to combat morning sickness?", the AI ​​will refer to other data that matches the user's profile (for example, the number of weeks pregnant) and provide specific measures, such as "Diets containing ginger are effective."

[0378] 5. Health data management and monitoring measures

[0379] Users enter their own and their children's health information (weight, body temperature, dietary details, etc.) into the device.

[0380] The device sends this data to a server, which then uses AI to analyze the data and monitor the user's health.

[0381] Examples:

[0382] Users enter their daily weight, and the server analyzes the data and sends alerts if their weight is increasing too rapidly.

[0383] 6. Mental health support measures

[0384] The server periodically sends a stress check questionnaire to the user's device and collects the results.

[0385] The AI ​​will analyze the survey responses and suggest relaxation and stress reduction methods as needed.

[0386] Examples:

[0387] If the user answers the questionnaire indicating high stress, the server will suggest "relaxation breathing techniques."

[0388] 7. Community Recommendations

[0389] The server recommends appropriate online communities based on the user's profile.

[0390] Users can join recommended communities and share information and experiences with other members.

[0391] Examples:

[0392] New moms are encouraged to join the "First Time Parenting Community" where they can share information and experiences with other new moms.

[0393] 8. Photo analysis and album generation method

[0394] Users upload ultrasound images and photos of their child's growth record to the device.

[0395] The server uses facial recognition technology to analyze the photos and select the most important ones.

[0396] A digital album is automatically generated based on the selected photos.

[0397] Examples:

[0398] When users upload one ultrasound photo per month, the server organizes them in chronological order and creates a growth record album.

[0399] Combining Emotion Engines

[0400] 9. Emotion Recognition with Emotion Engine

[0401] Users can input their daily moods and emotions through the device, and emotions can also be recognized through voice input and facial expression capture.

[0402] The device sends this emotional data to the server, which then analyzes it using an emotion engine.

[0403] Examples:

[0404] When a user uses the diary function and enters "I'm very tired today," the emotion engine understands "tired" and the server stores that data.

[0405] 10. Personalized advice based on emotional data

[0406] The server adjusts the content and tone of the advice based on the user's emotional data recognized by the emotion engine. For example, if the user is feeling stressed, the server will provide encouraging advice in a gentle tone.

[0407] Users can receive more personalized advice through their devices.

[0408] Examples:

[0409] If the user types "I'm frustrated," the server will offer gentle advice like "Try to relax a bit today."

[0410] 11. Strengthening mental health support

[0411] The emotion engine combines the results of traditional stress tests with emotional data to provide a more accurate mental health assessment.

[0412] Based on this, the server provides more appropriate relaxation methods and necessary support.

[0413] Examples:

[0414] If the user shows high stress in the stress check and the emotional data indicates "anxiety," the server will not only provide "deep breathing and meditation" methods but also recommend "booking a counseling appointment."

[0415] Through the above components and processes, this system comprehensively provides the information and support needed at each stage of pregnancy, childbirth, and child-rearing. This allows each user to not only obtain the information that is most suited to them, but also receive psychological support tailored to their emotions. Furthermore, by sharing information with other users in the same situation through the community function, users can receive even more comprehensive support.

[0416] The processing flow will be explained below.

[0417] 1. Generating information about pregnancy, childbirth, and child-rearing

[0418] Step 1:

[0419] The server periodically collects data from external medical databases and the latest research papers.

[0420] Specific operation: The server retrieves information from medical journals and databases via API and stores it in an internal database.

[0421] Step 2:

[0422] The server inputs the collected data into AI to generate information about pregnancy, childbirth, and child-rearing.

[0423] Specific operation: The AI ​​analyzes the collected data and uses a natural language generation algorithm to create sentences that are easy for users to understand.

[0424] Step 3:

[0425] The server distributes the generated information through a user interface (app or website).

[0426] Specific operation: The generated articles and information pages are uploaded to a web server so that users can access them.

[0427] 2. Providing personalized advice to users

[0428] Step 1:

[0429] Users enter their profile information into the device (e.g., age, number of weeks pregnant, health status).

[0430] Specific operation: The device displays a profile entry form, and once the profile entry is complete, it sends the data to the server.

[0431] Step 2:

[0432] The user inputs a specific question into the terminal.

[0433] Specific operation: The terminal displays a question form, and when the user enters a question and presses the send button, the question data is sent to the server.

[0434] Step 3:

[0435] The server inputs the user's profile information and questions into the AI ​​to generate personalized advice.

[0436] What it does: The AI ​​searches the database and creates personalized advice based on relevant information.

[0437] Step 4:

[0438] The server transmits the generated advice to the user terminal.

[0439] Specific operation: The created answer is delivered to the device in real time.

[0440] 3. Health care for mothers and children

[0441] Step 1:

[0442] Users input their daily health data (weight, body temperature, dietary content, etc.) into the device.

[0443] Specific operation: The terminal provides an input interface, and after data is entered, the data is sent to the server by pressing the send button.

[0444] Step 2:

[0445] The terminal transmits the input data to the server.

[0446] Specific operation: The device sends data to the server via an HTTP request or API.

[0447] Step 3:

[0448] The server analyzes the received data using AI and monitors the health status.

[0449] What it does: The AI ​​analyzes the data, checks for any anomalies, and runs algorithms to assess whether it's within the normal range.

[0450] Step 4:

[0451] The server generates feedback for the user based on the analysis results and sends it to the device.

[0452] Specific operation: Analysis results and recommended actions are sent to the device in real time.

[0453] 4. Mental health support

[0454] Step 1:

[0455] The server periodically sends a stress check questionnaire to the terminal.

[0456] Specific operation: The server generates a stress check form and sends it to the terminal based on the specified schedule.

[0457] Step 2:

[0458] The user answers the questionnaire and enters it into the terminal.

[0459] Specific operation: The terminal provides an interface for answering the survey questions, and after entering the answer, displays a submit button.

[0460] Step 3:

[0461] The terminal sends the questionnaire responses to the server.

[0462] Specific operation: The device sends the response data to the server via an HTTP request or API.

[0463] Step 4:

[0464] The server analyzes the response data using AI and evaluates stress levels.

[0465] What it does: The AI ​​analyzes your answers and runs an algorithm to quantify your stress level.

[0466] Step 5:

[0467] Based on the analysis results, the server suggests relaxation methods and sends them to the device.

[0468] Specific operation: Generate proposal content and send it to the terminal.

[0469] 5. Community Recommendations

[0470] Step 1:

[0471] The server recommends appropriate communities based on the user's profile.

[0472] Specific Operation: The server parses the profile information and generates a list of appropriate communities.

[0473] Step 2:

[0474] Users join recommended communities.

[0475] Specific operation: The terminal provides a participation interface and displays a participation button.

[0476] Step 3:

[0477] Users share information and experiences within the community.

[0478] Specific operation: The device provides messaging and posting functions to share information with other users.

[0479] 6. Memories storage

[0480] Step 1:

[0481] Users upload ultrasound images and photos of their child's growth record to the device.

[0482] Specific operation: The terminal provides a photo upload interface and sends the uploaded photo data to the server.

[0483] Step 2:

[0484] The server analyzes the uploaded photos using facial recognition technology.

[0485] How it works: The AI ​​analyzes the photo data and runs an algorithm to identify important people in the photos.

[0486] Step 3:

[0487] The server selects important photos and generates an automatic album.

[0488] Specific operation: Organize photos chronologically and generate a digital album layout for the user.

[0489] Step 4:

[0490] The server transmits the generated album to the terminal.

[0491] Specific Actions: Create a digital album and provide a link for users to access it.

[0492] 7. Emotion Recognition with Emotion Engine

[0493] Step 1:

[0494] Users can input their moods and emotions into the device, and voice input and facial recognition are also available for facial expression capture.

[0495] Specific operation: The device provides an emotion input interface and collects voice and facial expression data.

[0496] Step 2:

[0497] The terminal transmits the emotion data to the server.

[0498] Specific operation: Sends voice and facial expression data to the server via HTTP request or API.

[0499] Step 3:

[0500] The server uses an emotion engine to analyze the transmitted emotion data.

[0501] Specific operation: Analyzes data using emotion recognition algorithms to determine the user's emotional state.

[0502] 8. Personalized advice based on emotional data

[0503] Step 1:

[0504] The server adjusts the content and tone of the advice based on the emotional data recognized by the emotion engine.

[0505] Specific operation: The newly acquired emotion data is applied to the advice generation algorithm to generate appropriate advice.

[0506] Step 2:

[0507] The server transmits the generated advice to the user terminal.

[0508] Specific operation: Advice content is delivered to the device in real time.

[0509] 9. Strengthening mental health support

[0510] Step 1:

[0511] The emotion engine integrates stress check results with emotional data to provide a more accurate mental health assessment.

[0512] How it works: An analytical algorithm combines stress levels and emotional data to assess your overall mental health.

[0513] Step 2:

[0514] Based on the overall evaluation results, the server will suggest further appropriate relaxation methods and support.

[0515] Specific operation: Generate proposal content and send it to the terminal.

[0516] Through the above processing steps, information and support related to pregnancy, childbirth, and child-rearing are provided to users. By utilizing the emotion engine, the system effectively supports the user's mental health and provides personalized information and advice according to their physical condition and emotions.

[0517] Example 2

[0518] 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."

[0519] Conventional information systems related to pregnancy, childbirth, and child-rearing have struggled to provide information and advice tailored to each user's individual circumstances and emotions. Furthermore, methods for comprehensively supporting users' mental health have been limited. Furthermore, there is a need for a comprehensive system that can provide a wide range of support, including photo management and community recommendation functions.

[0520] 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.

[0521] In this invention, the server includes means for collecting user data, means for generating information about pregnancy, childbirth, and child-rearing based on the collected data, means for distributing the generated information to users, means for generating and providing personalized advice based on user questions, means for collecting, analyzing, and monitoring individual health information, means for analyzing emotional data and suggesting relaxation methods as needed to support the user's mental health, means for recommending communities and sharing information among users, means for analyzing uploaded image data, selecting appropriate photos, and generating albums, means for collecting and analyzing user emotional data using an emotion engine, and means for providing personalized advice based on the analyzed emotional data. This allows users to receive information and support optimized for their own situation and emotions.

[0522] "User data" refers to information about system users, including profile information, health status, number of weeks pregnant, and past medical history.

[0523] "Means for collecting" refers to a method or device for having a user input data, transmitting it from the terminal to a server, and storing it in a database.

[0524] "Means for generating information" refers to methods and devices that use AI or servers to create useful information about pregnancy, childbirth, and child-rearing based on collected data.

[0525] The "means for distributing" refers to a method or device for distributing the generated information to a user's terminal.

[0526] "Personalized advice" refers to advice or suggestions that are tailored to a user's specific situation based on their individual information.

[0527] "Means for collecting, analyzing, and monitoring health information" refers to methods and devices that collect and analyze data related to the health of users and their children, and monitor the results regularly.

[0528] "Means for suggesting relaxation methods to support mental health" refers to a method or device that analyzes the user's emotions and stress state and suggests appropriate relaxation methods or stress reduction measures based on the results.

[0529] "Means for recommending communities and sharing information" refers to a method or device for recommending appropriate online communities based on user profile data and supporting information exchange among users within those communities.

[0530] "Means for analyzing image data and generating an album" refers to a method or device that analyzes photos and image data uploaded by users, selects important images, and automatically generates a digital album.

[0531] An "emotion engine" refers to software or algorithms that recognize and analyze emotions from user input data, voice, facial expression data, etc.

[0532] This invention combines an emotion engine with a comprehensive support system for pregnancy, childbirth, and child-rearing to recognize the user's emotions and provide more accurate, personalized support. The system uses AI technology to collect user data and provides personalized information and advice based on that data. In particular, the invention aims to utilize the user's emotion data to more accurately understand the user's mental health and overall well-being and provide appropriate support tailored to the user's needs.

[0533] How user data is collected

[0534] The user enters their profile information into the device, such as their age, number of weeks pregnant, health status, and past medical history.

[0535] The terminal sends this information to a server, which stores it in a database. The software used here is a database management system (DBMS).

[0536] Information generation means

[0537] The server periodically collects data from external medical databases and the latest research papers and stores it in an internal database.

[0538] The AI ​​uses the collected data to generate up-to-date information about pregnancy, childbirth, and parenting, which is then presented through a user interface. The software used is an AI model equipped with natural language processing (NLP) algorithms.

[0539] Information distribution method

[0540] The server distributes the generated information through a user interface (app or website).

[0541] Users can access this information through an app or web interface. The software used here is a web application framework and a mobile application platform.

[0542] Personalized advice delivery methods

[0543] A user enters a specific question into the terminal, which then transmits the question to the server.

[0544] The server uses AI to generate personalized advice based on the user's profile information and questions, and sends the answer to the device.

[0545] Examples:

[0546] When a user asks, "What can I do to combat morning sickness?", the AI ​​will refer to other data that matches the user's profile (e.g., number of weeks pregnant) and provide specific measures such as "Diets containing ginger are effective." An example of a prompt sentence in this case is, "What can I do to combat morning sickness?"

[0547] Health data management and monitoring tools

[0548] Users enter their own and their children's health information (weight, body temperature, dietary details, etc.) into the device.

[0549] The device sends this data to a server, which then uses AI to analyze the data and monitor the user's health.

[0550] Examples:

[0551] When a user enters their daily weight, the server analyzes the data and sends a warning if their weight is increasing rapidly. An example of a prompt sentence is "Your weight today is 80 kg."

[0552] Mental health support measures

[0553] The server periodically sends a stress check questionnaire to the user's device and collects the results.

[0554] The AI ​​will analyze the survey responses and suggest relaxation and stress reduction methods as needed.

[0555] Examples:

[0556] If the user answers the questionnaire indicating high stress, the server will suggest "breathing exercises for relaxation." An example of a prompt is "How often have you felt stressed recently?"

[0557] Community Recommendations

[0558] The server recommends appropriate online communities based on the user's profile.

[0559] Users can join recommended communities and share information and experiences with other members.

[0560] Examples:

[0561] New moms are encouraged to join a "first-time parenting community" where they can share information and experiences with other new moms. An example of a prompt is "Do you want to make mommy friends?"

[0562] Photo analysis and album generation tool

[0563] Users upload ultrasound images and photos of their child's growth record to the device.

[0564] The server uses facial recognition technology to analyze the photos and select the most important ones.

[0565] A digital album is automatically generated based on the selected photos.

[0566] Examples:

[0567] When a user uploads one ultrasound photo per month, the server organizes them in chronological order and creates a growth record album. An example of a prompt is "Please upload this month's ultrasound photo."

[0568] Combining Emotion Engines

[0569] Emotion recognition by emotion engine

[0570] Users can input their daily moods and emotions through the device, and emotions can also be recognized through voice input and facial expression capture.

[0571] The device sends this emotional data to the server, which then analyzes it using an emotion engine.

[0572] Examples:

[0573] When a user uses the diary function and enters "I'm very tired today," the emotion engine understands "tired" and the server stores the data. An example of a prompt sentence is "Please tell me how you feel today."

[0574] Personalized advice based on emotional data

[0575] The server adjusts the content and tone of the advice based on the user's emotional data recognized by the emotion engine. For example, if the user is feeling stressed, the server will provide encouraging advice in a gentle tone.

[0576] Users can receive more personalized advice through their devices.

[0577] Examples:

[0578] If the user types "I'm frustrated," the server might offer gentle advice such as "Try to relax a bit today." An example of a prompt sentence is "I'm frustrated, what should I do?"

[0579] Strengthening mental health support

[0580] The emotion engine combines the results of traditional stress tests with emotional data to provide a more accurate mental health assessment.

[0581] Based on this, the server provides more appropriate relaxation methods and necessary support.

[0582] Examples:

[0583] If the user's stress check indicates high stress and the emotional data indicates "anxiety," the server will not only provide "deep breathing and meditation" methods but also recommend "booking a counseling appointment." An example of a prompt sentence is, "I've been feeling a lot of anxiety lately. What should I do?"

[0584] Through the above components and processes, this system comprehensively provides the information and support needed at each stage of pregnancy, childbirth, and child-rearing. This allows each user to not only obtain the information that is most suited to them, but also receive psychological support tailored to their emotions. Furthermore, by sharing information with other users in the same situation through the community function, users can receive even more comprehensive support.

[0585] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0586] Step 1: Enter and submit user data

[0587] The user enters their profile information into the device, such as age, pregnancy status, health status, and past medical history.

[0588] Input: User profile information

[0589] The terminal sends the entered information to the server. Specifically, when data is entered through a form and the send button is pressed, the data is sent to the server in real time.

[0590] Output: User data sent to the server

[0591] Specific operation: The user enters information into the profile entry screen of the app and presses the send button. The device then sends the data to the server.

[0592] Step 2: Save user data

[0593] The server receives the user data sent from the terminal and stores it in a database using a database management system (DBMS).

[0594] Input: User data sent from the terminal

[0595] Output: User data stored in the database

[0596] Specific operation: The server uses the database API to retrieve the received data and save it in the database.

[0597] Step 3: Collect medical data

[0598] The server collects data from external medical databases and the latest research papers and stores it in an internal database.

[0599] Input: External medical databases and research papers

[0600] Output: Medical data stored in an internal database

[0601] Specific operation: The server periodically collects medical data using an external API and stores it in its own database.

[0602] Step 4: Information Generation

[0603] The AI ​​built into the server generates the latest information on pregnancy, childbirth, and child-rearing based on user and medical data.

[0604] Input: User data, medical data

[0605] Output: Latest information generated

[0606] How it works: The AI ​​model analyzes the user's profile information and the latest medical data to generate information appropriate for the user.

[0607] Step 5: Distributing information

[0608] The server delivers the generated information to the user through a user interface (app or website).

[0609] Input: Latest generated information

[0610] Output: Information delivered to the user

[0611] Specific behavior: The server generates information and sends it to a user interface using an API to display it on the app's home screen or website dashboard.

[0612] Step 6: Enter and submit your specific question

[0613] The user types a specific question into the device, such as "Please tell me what to do about morning sickness."

[0614] Input: User's specific question

[0615] The terminal sends a query to the server.

[0616] Output: The query data sent to the server

[0617] Specific operation: The user enters a specific question into the question input field of the app and presses the send button. The device then sends the question data to the server.

[0618] Step 7: Generate personalized advice

[0619] The server uses AI to generate personalized advice based on the user's profile information and questions.

[0620] Input: User profile information, specific questions

[0621] Output: Generated personalized advice

[0622] How it works: The AI ​​model references the user's profile and question to generate the most appropriate advice.

[0623] Step 8: Distributing Advice

[0624] The server transmits the generated advice to the terminal.

[0625] Input: Generated personalized advice

[0626] Output: Advice delivered to the terminal

[0627] Specific operation: The server uses an API to send the generated advice data to the terminal and notifies the user's terminal.

[0628] Step 9: Enter and submit your health information

[0629] Users enter their own and their children's health information into the device, such as weight, body temperature, and dietary details.

[0630] Input: Health information

[0631] The terminal transmits this data to the server.

[0632] Output: Health data sent to the server

[0633] Specific operation: The user enters health information into the app and presses the send button. The device then sends the data to the server.

[0634] Step 10: Health data storage and analysis

[0635] The server stores the submitted health data in a database and analyzes it using AI.

[0636] Input: Health data

[0637] Output: Analyzed health data

[0638] How it works: The server receives health data and stores it in a database. The AI ​​model analyzes the data and monitors for abnormalities.

[0639] Step 11: Submit the stress check questionnaire

[0640] The server periodically sends a stress check questionnaire to the user's terminal.

[0641] Input: Stress check questionnaire

[0642] Output: Survey sent to user's device

[0643] Specific operation: The server uses an API to send stress check questionnaire data to the terminal and submits questionnaires to the user at high frequency.

[0644] Step 12: Complete and submit the survey

[0645] The user answers the stress check questionnaire.

[0646] Input: Stress check questionnaire response

[0647] The terminal sends the response to the server.

[0648] Output: Survey responses sent to the server

[0649] Specific operation: The user answers the questionnaire and presses the send button. The device sends the answer data to the server.

[0650] Step 13: Analyze stress data and propose relaxation methods

[0651] The server uses AI to analyze the questionnaire responses and suggest relaxation methods as needed.

[0652] Input: Survey response data

[0653] Output: Proposed relaxation method

[0654] Specific operation: The AI ​​model analyzes stress data, devises stress reduction measures, and suggests them to the user.

[0655] Step 14: Community Recommendations

[0656] The server recommends appropriate online communities based on the user's profile.

[0657] Input: User profile information

[0658] Output: Community recommendations

[0659] Specific operation: The server analyzes the profile information and generates a list of recommended communities.

[0660] Step 15: Upload and analyze photos

[0661] Users upload ultrasound images and photos of their child's growth record to the device.

[0662] Input: Ultrasound photos and growth record photos

[0663] The device sends the photo to the server.

[0664] Output: Photo data sent to the server

[0665] Specific operation: The user uploads a photo in the specified location in the app, and the device sends it to the server.

[0666] Step 16: Create an album

[0667] The server uses facial recognition technology to analyze the photos, select important photos, and generate a digital album.

[0668] Input: Photo data

[0669] Output: Digital album

[0670] Specific operation: The server analyzes the photo data, organizes it chronologically, and generates a growth record album.

[0671] Step 17: Enter and send emotion data

[0672] The user inputs emotions into the device, including voice input and facial expression capture.

[0673] Input: Emotion data

[0674] The terminal transmits the emotion data to the server.

[0675] Output: Emotion data sent to the server

[0676] Specific operation: The user inputs data expressing emotions into the terminal, and the terminal transmits the data to the server.

[0677] Step 18: Analyze and store emotion data

[0678] The server uses an emotion engine to analyze the emotion data and saves the results.

[0679] Input: Emotion data

[0680] Output: Parsed emotion data

[0681] Specific operation: The emotion engine analyzes the emotion data and stores it in the server's database.

[0682] Step 19: Generating personalized advice based on sentiment data

[0683] The server adjusts the content and tone of the advice based on the emotional data recognized by the emotion engine.

[0684] Input: Parsed emotion data

[0685] Output: Adjusted advice

[0686] Specific operation: The AI ​​generates advice that reflects emotional data and provides it in a form appropriate for the user.

[0687] Step 20: Providing personalized advice

[0688] The server delivers the tailored advice to the user's terminal.

[0689] Input: Tailored Advice

[0690] Output: Advice delivered to the user's device

[0691] Specific operation: The server sends the generated advice data to the device so that the user can view it in the app.

[0692] In this way, the system provides comprehensive and personalized support to users while performing a wide range of data collection, analysis, information generation and distribution.

[0693] (Application example 2)

[0694] 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."

[0695] Support systems for pregnancy, childbirth, and child-rearing are required to accurately grasp the emotional state and health information of individual users and provide appropriate advice and support in real time. However, conventional systems have difficulty responding to emotional changes in a personalized manner, and have not been able to provide sufficient satisfaction to users. Furthermore, to improve the quality of advice in physical stores, flexible responses according to the customer's emotional state are necessary.

[0696] 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 user data, means for generating information about pregnancy, childbirth, and child-rearing based on the collected data, means for distributing the generated information to the user, means for generating and providing personalized advice based on the user's questions, means for managing, analyzing, and monitoring health data of the mother and child, means for conducting and analyzing stress checks to support the user's mental health and suggesting appropriate relaxation methods, means for recommending communities and allowing users to share information, means for analyzing uploaded photos, selecting appropriate photos, and generating albums, means for analyzing the user's emotional state based on emotional data and adjusting the content and tone of personalized advice, and means for recognizing customer emotions in real time at a physical store and providing individual counseling and advice tailored to the situation. This allows users to receive personalized advice and support in real time based on their emotions and health condition.

[0697] "User Data" is a set of data about a user, such as the user's profile information, health information, and emotional state.

[0698] A "means for collecting" is a method or device for inputting, obtaining, or detecting user data.

[0699] The "means for generating information" refers to a method or device for generating information related to pregnancy, childbirth, and child-rearing based on collected user data.

[0700] "Means for distributing information" refers to a method or device for providing the generated information to users.

[0701] "Personalized advice" is advice that is specifically tailored to a user's question or situation.

[0702] "Health data" refers to data such as the weight, temperature, and health status of the mother and child.

[0703] "Management, analysis and monitoring means" refers to a set of methods or devices for collecting health data, analyzing and monitoring it, and providing appropriate support to users.

[0704] A "stress check" is a questionnaire or assessment conducted to assess a user's mental health.

[0705] "Relaxation techniques" refer to breathing techniques, meditation, relaxation techniques, etc. that are used to reduce mental stress.

[0706] A "community" is a group or online forum where users with a common interest share information and experiences.

[0707] The "means for analyzing photos and generating an album" refers to a method or device for analyzing uploaded photos, selecting important images, and creating a digital album.

[0708] "Emotion data" is data that indicates the user's daily mood and emotional state.

[0709] The "means for analyzing emotional state" refers to a method or device for recognizing and evaluating the user's emotions based on emotional data.

[0710] A "brick and mortar store" is a physical store where customers receive goods or services in person.

[0711] A "means for recognizing customer emotions in real time" is a method or device that can instantly grasp a customer's current emotions.

[0712] "Means for providing counseling and advice" refers to a method or device that provides appropriate support in response to the user's feelings and questions.

[0713] This invention is a comprehensive support system for pregnancy, childbirth, and child-rearing, which recognizes the user's emotions by combining an emotion engine and provides more accurate and personalized support. An embodiment of this system will be described in detail below.

[0714] Hardware and software used

[0715] Hardware: smartphones, tablets, back-end servers

[0716] Software: Emotion recognition engine, AI model (e.g., TensorFlow, GPT-3), database (e.g., MySQL, Firebase), user interface (e.g., Vue.js, React Native)

[0717] System Program

[0718] First, user data is collected, where users enter their profile information, health information, and daily emotional state using a smartphone or tablet device, and this data is sent in real time to a back-end server and stored in a database.

[0719] Next, AI generates information about pregnancy, childbirth, and child-rearing based on the collected data. It compares and analyzes user data stored in the database with data collected from external medical databases and the latest research papers. This generates the most up-to-date and accurate information and provides it to users.

[0720] The generated information is delivered to the user through an interface. When a user enters a question through an app or tablet, the question is sent to the server. The server uses AI to generate personalized advice based on the question and the user's profile information and sends it back to the device.

[0721] The user data also includes health data of the mother and child, which is managed, analyzed, and monitored by the server. If any abnormalities are found in the health data, warnings and countermeasures are automatically proposed.

[0722] Supporting mental health is also an important element. The server periodically sends users stress check questionnaires and analyzes their responses. The emotion engine recognizes the user's emotional state and then personalized suggestions are made for relaxation and stress reduction.

[0723] The system also has a photo analysis and album generation function. Ultrasound photos and growth record photos uploaded by users are analyzed using AI, and important photos are automatically selected and created as a digital album.

[0724] Finally, we will explain how this system can be applied to physical stores. When customers visit a physical store, they can input their emotional state on the spot using a smartphone or tablet, or their emotional state can be analyzed in real time by an emotion recognition engine. This information is immediately sent to a server, which then provides appropriate counseling or advice.

[0725] Examples of concrete examples and prompts

[0726] For example, if a customer visiting a physical store types in "I feel irritated while breastfeeding," the emotion engine will recognize the word "irritation," and the AI ​​model will suggest "simple breathing exercises to help you relax" based on profile data such as the number of weeks pregnant and health status. It will also recommend places to purchase relaxation products and nearby mental health support organizations.

[0727] Prompt Sentence Examples

[0728] Ask the AI ​​model the following prompt:

[0729] User profile data: Age: "30", Pregnancy week: "20 weeks", Health status: "Normal"

[0730] Emotional data: "I'm feeling very frustrated today."

[0731] Q: "What can I do to reduce frustration while breastfeeding?"

[0732] Answer: "Try some breathing exercises to help you relax, especially taking deep breaths. Also, consider using relaxation aids."

[0733] In this way, the embodiments of the invention can provide personalized advice and support in real time according to the user's emotions and health condition.

[0734] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0735] Step 1:

[0736] A user uses a smartphone or tablet device to input their profile information, health information, and daily emotional state. This includes age, pregnancy week, health condition, and emotion (e.g., "I'm irritated"). The input data is sent from the device to a server in real time. The server receives this data and stores it in a database. Here, the input is the user's profile information and emotional data, and the output is the user data stored in the database.

[0737] Step 2:

[0738] The server generates information about pregnancy, childbirth, and child-rearing based on user data stored in the database and data collected from external medical databases and the latest research papers. An AI model (e.g., TensorFlow or GPT-3) processes this information and generates up-to-date and accurate information. The input is user data and external data, and the output is the generated up-to-date information.

[0739] Step 3:

[0740] The server delivers the generated information to the user, who then displays it on their smartphone or tablet through a user interface (e.g., Vue.js, React Native). The input is the generated up-to-date information, and the output is the information displayed in the user interface.

[0741] Step 4:

[0742] The user inputs a specific question via an app or tablet. For example, "What can I do if I get irritated while breastfeeding?" The input question is sent from the device to the server. The server uses an AI model to generate personalized advice based on the question and the user's profile information, and sends it back to the device. The input is the user's question and profile information, and the output is personalized advice.

[0743] Step 5:

[0744] The health data of the user's mother and child is managed, analyzed, and monitored by a server. The user enters health data (e.g., weight, temperature) into the device and sends it to the server. The server analyzes this data using AI, and if any abnormalities are detected, it automatically issues warnings and suggests countermeasures. The input is health data, and the output is the analysis results and countermeasures.

[0745] Step 6:

[0746] The server periodically sends a stress check questionnaire to the user's device. The user answers the questionnaire and the data is sent to the server. The server uses an emotion recognition engine to analyze the user's emotional state and suggests relaxation methods and stress reduction measures. The input is the questionnaire response data and emotional data, and the output is the suggested relaxation methods.

[0747] Step 7:

[0748] The server recommends suitable online communities to users through the community function. It selects and recommends relevant communities based on the user's profile information. The input is the user's profile information, and the output is the recommended communities.

[0749] Step 8:

[0750] Users upload ultrasound images and growth record photos to their device. The server uses AI to analyze them, selects important photos, and generates a digital album. The input is the uploaded photos, and the output is the generated digital album.

[0751] Step 9:

[0752] In physical stores, customers input their emotional state using a smartphone or tablet, and the device's emotion recognition engine analyzes their emotional state in real time. The information is immediately sent to the server, which then provides appropriate counseling and advice. The input is the emotional data of the physical store customer, and the output is real-time counseling and advice.

[0753] 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.

[0754] 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.

[0755] 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.

[0756] [Second embodiment]

[0757] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0758] 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.

[0759] 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).

[0760] 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.

[0761] 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.

[0762] 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).

[0763] 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.

[0764] 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.

[0765] 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.

[0766] 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.

[0767] 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.

[0768] 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."

[0769] This invention is a system that provides a series of information and support related to pregnancy, childbirth, and child-rearing, and its core is information generation and personalization using AI technology. The components of this system consist of various means for collecting user data and providing information and advice generated based on that data.

[0770] Overview of program processing

[0771] 1. How we collect user data

[0772] Users first enter their profile information into the device, including their age, number of weeks pregnant, health status, and past medical history.

[0773] The terminal sends this information to the server, which stores it in a database.

[0774] 2. Information generation means

[0775] The server periodically collects data from external medical databases and the latest research papers and stores it in an internal database.

[0776] The AI ​​uses the collected data to generate up-to-date information on pregnancy, childbirth, and parenting, which is then presented through an interface for users to access.

[0777] 3. Information distribution methods

[0778] The server sends the generated information to the device for viewing by the user, who can access this information through an app or web interface.

[0779] 4. Means of personalized advice delivery

[0780] A user enters a specific question into the terminal, which then transmits the question to the server.

[0781] The server uses AI to generate personalized advice based on the user's profile information and questions, and sends the answer to the device.

[0782] Examples:

[0783] When a user asks, "What can I do to combat morning sickness?", the AI ​​will refer to other data that matches the user's profile (for example, the number of weeks pregnant) and provide specific measures, such as "Diets containing ginger are effective."

[0784] 5. Health data management and monitoring measures

[0785] Users enter their own and their children's health information (weight, body temperature, dietary details, etc.) into the device.

[0786] The device sends this data to a server, which then uses AI to analyze the data and monitor the user's health.

[0787] Examples:

[0788] Users enter their daily weight, and the server analyzes the data and sends alerts if their weight is increasing too rapidly.

[0789] 6. Mental health support measures

[0790] The server periodically sends a stress check questionnaire to the user's device and collects the results.

[0791] The AI ​​will analyze the survey responses and suggest relaxation and stress reduction methods as needed.

[0792] Examples:

[0793] If the user answers the questionnaire indicating high stress, the server will suggest "relaxation breathing techniques."

[0794] 7. Community Recommendations

[0795] The server recommends appropriate online communities based on the user's profile.

[0796] Users can join recommended communities and share information and experiences with other members.

[0797] Examples:

[0798] New moms are encouraged to join the "First Time Parenting Community" where they can share information and experiences with other new moms.

[0799] 8. Photo analysis and album generation method

[0800] Users upload ultrasound images and photos of their child's growth record to the device.

[0801] The server uses facial recognition technology to analyze the photos and select the most important ones.

[0802] A digital album is automatically generated based on the selected photos.

[0803] Examples:

[0804] When users upload one ultrasound photo per month, the server organizes them in chronological order and creates a growth record album.

[0805] Through the above components and processes, this system comprehensively provides the information and support needed at each stage of pregnancy, childbirth, and child-rearing. This allows each user to not only obtain the information that is most suitable for them, but also receive psychological support. Furthermore, by sharing information with other users in the same situation through the community function, users can receive even more comprehensive support.

[0806] The processing flow will be explained below.

[0807] 1. Generating information about pregnancy, childbirth, and child-rearing

[0808] Step 1:

[0809] The server periodically collects data from external medical databases and the latest research papers.

[0810] Specific operation: The server retrieves information from medical journals and other medical sources through APIs and stores it in an internal database.

[0811] Step 2:

[0812] The server inputs the collected data into AI to generate information about pregnancy, childbirth, and child-rearing.

[0813] Specific operation: The AI ​​analyzes the collected data and uses a natural language generation algorithm to create sentences that are easy for users to understand.

[0814] Step 3:

[0815] The server distributes the generated information through a user interface (app or website).

[0816] Specific operation: The generated articles and information pages are uploaded to a web server so that users can access them.

[0817] 2. Providing personalized advice to users

[0818] Step 1:

[0819] Users enter their profile information into the device (e.g., age, number of weeks pregnant, health status).

[0820] Specific operation: The device displays a profile entry form and, once completed, sends the data to the server.

[0821] Step 2:

[0822] The user inputs a specific question into the terminal.

[0823] Specific operation: The terminal displays a question form, and when the user enters a question and presses the send button, the question data is sent to the server.

[0824] Step 3:

[0825] The server inputs the user's profile information and questions into the AI ​​to generate personalized advice.

[0826] What it does: The AI ​​searches the database and creates personalized advice based on relevant information.

[0827] Step 4:

[0828] The server transmits the generated advice to the user terminal.

[0829] Specific operation: The created answer is delivered to the device in real time.

[0830] 3. Health care for mothers and children

[0831] Step 1:

[0832] Users input their daily health data (weight, body temperature, dietary content, etc.) into the device.

[0833] Specific operation: The terminal provides an input interface, and after data is entered, pressing the send button sends the data to the server.

[0834] Step 2:

[0835] The terminal transmits the input data to the server.

[0836] Specific operation: The device sends data to the server via an HTTP request or API.

[0837] Step 3:

[0838] The server analyzes the received data using AI and monitors the health status.

[0839] What it does: The AI ​​analyzes the data, checks for any anomalies, and runs algorithms to assess whether it's within the normal range.

[0840] Step 4:

[0841] The server generates feedback for the user based on the analysis results and sends it to the device.

[0842] Specific operation: Analysis results and recommended actions are sent to the device in real time.

[0843] 4. Mental health support

[0844] Step 1:

[0845] The server periodically sends a stress check questionnaire to the terminal.

[0846] Specific operation: The server generates a stress check form and sends it to the terminal on the specified schedule.

[0847] Step 2:

[0848] The user answers the questionnaire and enters it into the terminal.

[0849] Specific operation: The terminal provides an interface for answering the survey questions and displays a button to submit the answers.

[0850] Step 3:

[0851] The terminal sends the questionnaire responses to the server.

[0852] Specific operation: Survey response data is sent to the server via HTTP request or API.

[0853] Step 4:

[0854] The server analyzes the response data using AI and evaluates stress levels.

[0855] What it does: The AI ​​analyzes your answers and runs an algorithm to quantify your stress level.

[0856] Step 5:

[0857] Based on the analysis results, the server suggests relaxation methods and sends them to the device.

[0858] Specific operation: Generate proposal content and send it to the terminal.

[0859] 5. Community Recommendations

[0860] Step 1:

[0861] The server recommends appropriate communities based on the user's profile.

[0862] Specific Operation: The server parses the profile information and generates a list of appropriate communities.

[0863] Step 2:

[0864] Users join recommended communities.

[0865] Specific operation: The terminal provides a participation interface and displays a participation button.

[0866] Step 3:

[0867] Users share information and experiences within the community.

[0868] Specific operation: The device provides messaging and posting functions to share information with other users.

[0869] 6. Memories storage

[0870] Step 1:

[0871] Users upload ultrasound images and photos of their child's growth record to the device.

[0872] Specific operation: The terminal provides a photo upload interface and sends the uploaded photos to the server.

[0873] Step 2:

[0874] The server analyzes the uploaded photos using facial recognition technology.

[0875] How it works: The AI ​​analyzes the photo data and runs an algorithm to identify important people in the photos.

[0876] Step 3:

[0877] The server selects important photos and generates an automatic album.

[0878] Specific operation: Organize photos chronologically and generate a digital album layout for the user.

[0879] Step 4:

[0880] The server transmits the generated album to the terminal.

[0881] Specific Actions: Create a digital album and provide a link for users to access it.

[0882] Example 1

[0883] 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."

[0884] Conventional information systems related to pregnancy, childbirth, and child-rearing only provide general information, making it difficult for individual users to obtain information and advice that is optimized for them. Furthermore, centralized management of health data and mental health support were insufficient, making it impossible to provide the comprehensive support that users need.

[0885] 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.

[0886] In this invention, the server includes a means for collecting user data, a means for generating information about pregnancy, childbirth, and child-rearing based on the collected data, and a means for distributing the generated information to the user. This enables personalized information and support. The system also includes a means for generating and providing personalized advice based on the user's questions, a means for managing, analyzing, and monitoring health data, a means for conducting and analyzing stress checks to support the user's mental health, and suggesting appropriate relaxation methods, a means for recommending online communities and allowing users to share information, and a means for analyzing uploaded images, selecting appropriate images, and generating a digital album. This allows users to receive comprehensive, personalized support, providing multifaceted support such as health management, mental health care, and promoting information sharing.

[0887] "User data" refers to data including profile information, health information, questions, etc. entered by the user.

[0888] "Information generation" is the process of generating information about pregnancy, childbirth, and parenting based on collected data.

[0889] "Information distribution" is the process of sending the generated information to the user's terminal and making it viewable.

[0890] "Personalized advice" is specific advice that is generated based on a user's individual questions and profile information.

[0891] "Health data management" is the process of collecting, analyzing, and monitoring user and child health information.

[0892] "Mental health support" is the process of conducting stress checks, analyzing stress levels, and suggesting appropriate relaxation methods to support the mental health of users.

[0893] "Online community recommendation" is the process of recommending appropriate communities based on a user's profile and encouraging them to join.

[0894] "Digital album generation" is the process of analyzing uploaded images, selecting important images, and creating a digital album.

[0895] "External data collection" is the process of obtaining data from external medical databases and research materials and storing it in an internal database.

[0896] "Personalized advice" refers to customized advice generated based on a user's profile information, health status, pregnancy stage, and health concerns.

[0897] MODE FOR CARRYING OUT THE INVENTION

[0898] This invention is a comprehensive system for providing information and support related to pregnancy, childbirth, and child-rearing, and utilizes AI technology to provide users with personalized information and advice. The purpose of this invention is to help users obtain the information they need in a timely and appropriate manner at each stage of their pregnancy and child-rearing lives.

[0899] 1. Collection of User Data

[0900] Users enter profile information such as age, number of weeks pregnant, health status, and past medical history into a device, which can be a smartphone, tablet, or PC.

[0901] The device sends the collected information to a server using a secure communication protocol (e.g., HTTPS).

[0902] The server validates the received data and stores it in a database, which can be an SQL database or a NoSQL database.

[0903] 2. Information Generation

[0904] The server periodically collects information from external medical databases (e.g., PubMed) and the latest research materials and stores them in an internal database.

[0905] AI models (e.g., GPT-3) analyze collected medical data and generate up-to-date information, including articles and advice on pregnancy, childbirth, and parenting.

[0906] 3. Information distribution

[0907] The server distributes the generated information to users, and in this process, the most appropriate information is selected based on each user's profile.

[0908] Users can access the information through an application or a web interface.

[0909] 4. Providing personalized advice

[0910] The user enters a specific question into the terminal and sends the question to the server.

[0911] The server uses AI to generate personalized advice based on the user's profile information and questions, and sends the answer to the device.

[0912] Example: When a user asks, "What can I do to prevent morning sickness?", the AI ​​will provide specific advice based on the user's number of weeks pregnant, such as "Diets that include ginger are effective."

[0913] 5. Health data management and monitoring

[0914] Users enter their daily health information (e.g., weight, body temperature, dietary details) into the device.

[0915] The terminal transmits this health information to the server.

[0916] The server uses AI to analyze the data and sends an alert if there is an abnormality.

[0917] Example: When a user enters their daily weight, the AI ​​analyzes changes in weight and, if there is a sudden increase, sends a warning to "consult a doctor."

[0918] 6. Mental health support

[0919] The server periodically sends a stress check questionnaire to the user's terminal.

[0920] The user answers the questionnaire and the results are sent to the server.

[0921] The AI ​​model will analyze the survey results and suggest relaxation and stress reduction methods as needed.

[0922] Example: If a user answers in a way that indicates high stress, the AI ​​will suggest "breathing techniques for relaxation."

[0923] 7. Community Recommendations

[0924] The server recommends appropriate online communities based on the user's profile.

[0925] Users join recommended communities and share information and experiences with other members.

[0926] Example: A new mother is recommended a "first-time parenting community."

[0927] 8. Photo analysis and album generation

[0928] Users upload ultrasound images and photos of their child's growth record to the device.

[0929] The server uses facial recognition technology to analyze the uploaded photos and select important ones.

[0930] The server generates a digital album based on the selected photos.

[0931] Example: When a user uploads one ultrasound photo per month, AI analyzes it, organizes it chronologically, and creates a digital album.

[0932] Through these components and processes, the system provides users with personalized information and support, enabling them to achieve the comprehensive support they need at each stage of pregnancy, childbirth, and child-rearing life.

[0933] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0934] Processing flow

[0935] Step 1: Enter user data

[0936] Users fill out a form in the application with profile information such as age, pregnancy stage, health status, and past medical history.

[0937] Input: Age, gestational age, health status, medical history

[0938] Output: Data entered by the user

[0939] Specific behavior: The user enters information into an input field and presses the "Submit" button.

[0940] Step 2: Send user data

[0941] The terminal transmits the input user information to the server.

[0942] Input: Data entered by the user

[0943] Output: Data sent to the server

[0944] Specific operation: The device sends data to the server using the HTTPS protocol.

[0945] Step 3: Save user data

[0946] The server validates the received user information and stores it in the database.

[0947] Input: Submitted user data

[0948] Output: Data stored in the database

[0949] What happens: The server checks the format and validity of the data and inserts it into the database.

[0950] Step 4: Gather external data

[0951] The server collects external medical databases and the latest research materials via API and stores them in an internal database.

[0952] Input: External databases and research materials

[0953] Output: Medical information stored in an internal database

[0954] Specific operation: The server periodically calls the API to collect new data and store it in the database.

[0955] Step 5: Information Generation

[0956] The AI ​​model generates up-to-date information on pregnancy, childbirth, and parenting based on collected medical data and user profiles.

[0957] Input: Medical information stored in an internal database, user profile

[0958] Output: Information provided to the user

[0959] What it does: AI models process data and generate reports and recommendations.

[0960] Step 6: Information distribution

[0961] The server transmits the generated information to the user's terminal.

[0962] Input: Information generated by the AI ​​model

[0963] Output: Information sent to the terminal

[0964] What it does: The server sends a notification to the user's device, making the information available in an app or web interface.

[0965] Step 7: Enter a specific question

[0966] The user enters a specific question into the terminal, which then transmits the question to the server.

[0967] Input: User's specific question

[0968] Output: The question sent to the server

[0969] Specific behavior: The user enters a question in the text box and presses the "Submit" button.

[0970] Step 8: Personalized advice generation

[0971] The server uses AI to generate personalized advice based on the user's questions and profile information and sends it to the device.

[0972] Input: User questions, profile information

[0973] Output: Personalized advice

[0974] What it does: The AI ​​model processes the data, generates specific advice, and sends it to the device.

[0975] Step 9: Enter and submit your health data

[0976] Users enter their daily health information into a terminal, which then transmits it to a server.

[0977] Input: Health information (weight, body temperature, dietary details, etc.)

[0978] Output: Health data sent to the server

[0979] Specific operation: The user enters health information in the app according to the format and presses the "Submit" button.

[0980] Step 10: Analyzing and monitoring health data

[0981] The server uses AI to analyze health data and sends an alert if there are any abnormalities.

[0982] Input: Collected health data

[0983] Output: Analysis results, warnings if necessary

[0984] What it does: The AI ​​model analyzes the data, detects abnormal patterns, generates alerts, and notifies the user.

[0985] Step 11: Mental Health Check

[0986] The server periodically sends a stress check questionnaire to the user, who then answers it.

[0987] Input: Stress check questionnaire response

[0988] Output: Analysis of survey results

[0989] Specific operation: The server sends a survey, the user answers, and the server receives and analyzes the answers.

[0990] Step 12: Suggested relaxation techniques

[0991] The AI ​​model analyzes the results of the stress check and suggests appropriate relaxation methods.

[0992] Input: Analysis results of stress check questionnaire

[0993] Output: Relaxation suggestions

[0994] Specific operation: The AI ​​model analyzes the data, generates the optimal relaxation method for the user, and notifies the device.

[0995] Step 13: Online Community Recommendations

[0996] The server recommends appropriate online communities based on the user's profile.

[0997] Input: User profile information

[0998] Output: Recommended community information

[0999] Specific operation: The server processes the data, selects the most suitable community for the user, and notifies them.

[1000] Step 14: Upload and analyze photos

[1001] Users upload ultrasound images and photos of their child's growth record to the device.

[1002] Input: Uploaded image

[1003] Output: Image data stored on the server

[1004] Specific behavior: The user selects a photo and presses the "Upload" button.

[1005] Step 15: Generate a digital album

[1006] The server uses facial recognition technology to analyze the images, select important images, and generate a digital album.

[1007] Input: Uploaded image data

[1008] Output: Generated digital album

[1009] Specific operation: The AI ​​model analyzes images and automatically generates an album to provide to the user.

[1010] Through these processing steps, the system provides users with personalized information and services, providing comprehensive support at each stage of pregnancy, childbirth, and child-rearing.

[1011] (Application example 1)

[1012] 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."

[1013] Previous information systems related to pregnancy, childbirth, and child-rearing were not able to assist users when selecting products in stores. This made it difficult for expectant mothers and parents to select the appropriate products they needed, and also increased the time and burden it took to search for products in stores. Furthermore, the lack of personalized product recommendations and optimal in-store routing based on individual users' profile information and health status meant that they were unable to provide an efficient and comfortable shopping experience.

[1014] 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.

[1015] In this invention, the server includes: means for collecting user data; means for generating information about pregnancy, childbirth, and child-rearing based on the collected data; means for distributing the generated information to users; means for generating and providing personalized advice based on user questions; means for managing, analyzing, and monitoring maternal and child health data; means for conducting and analyzing stress checks to support users' mental health and suggesting appropriate relaxation methods; means for recommending communities and allowing users to share information; means for analyzing uploaded photos, selecting appropriate photos, and creating albums; and means for recommending appropriate products and suggesting optimal in-store routing based on user profile information. This enables the provision of information and support tailored to the needs of individual users. It also makes it possible to streamline product searches in stores, providing a more comfortable and stress-free shopping experience.

[1016] "User Data" includes information about the user, such as profile information, health status, medical history, pregnancy weeks, and child ages.

[1017] "Information on pregnancy, childbirth, and child-rearing" refers to information related to health care, nutrition, child-rearing techniques, medical services, etc. for mothers and their children during pregnancy and after birth.

[1018] "Personalized advice" refers to providing customized advice tailored to a user's specific needs and circumstances based on their individual profile information and health status.

[1019] "Health data" refers to health-related information such as the weight, temperature, dietary habits, and medical records of the mother and child.

[1020] A "stress check" is a method of conducting a questionnaire or test to evaluate a user's mental state and analyzing the results.

[1021] "Relaxation methods" refer to specific techniques for reducing stress and achieving mental stability, such as breathing exercises and meditation.

[1022] A "community" refers to an online platform where users with similar circumstances can share information and experiences.

[1023] "Photo analysis" refers to the technology of analyzing image data uploaded by users and classifying or evaluating its content.

[1024] "Album generation" is the process of creating an automatically organized digital or physical photo album based on the analyzed photos.

[1025] "Product recommendation" is a means of selecting and suggesting products suitable for pregnancy and child-rearing based on the user's profile information.

[1026] "Routing" refers to providing optimal routes to help users efficiently find the desired product within a store.

[1027] This invention is a system that provides information and support related to pregnancy, childbirth, and child-rearing. This system collects user data and uses that data to generate information, provide advice, recommend products, and navigate within stores. Specific embodiments for implementing this system are described below.

[1028] 1. Collection of User Data

[1029] Using a device (such as a smartphone), the user enters their profile information, including age, number of weeks pregnant, health status, past medical history, and age of children. The device collects this information and sends it to a server, which stores the received data in a database.

[1030] 2. Information generation

[1031] The server periodically collects data from external medical databases and research papers and stores it in an internal database. Using AI technology, the server generates up-to-date information on pregnancy, childbirth, and parenting, and provides it through an interface for users to access. This AI technology includes, for example, generative AI models that utilize natural language processing (NLP).

[1032] 3. Information distribution

[1033] The generated information is sent from the server to the user's terminal, where the user can access the information through an application or web interface.

[1034] 4. Providing personalized advice

[1035] When a user types a specific question into the device, the question is sent to the server, where the AI ​​generates personalized advice based on the user's profile information and the question, and sends the answer back to the device.

[1036] 5. Health data management and monitoring

[1037] Users enter their own and their children's health information (weight, body temperature, dietary details, etc.) into the device. The device then sends this data to a server, which uses AI to analyze the data and monitor the health status. If any abnormalities, such as sudden weight gain, are detected, the server will send a warning to the user.

[1038] 6. Mental health support

[1039] The server periodically sends a stress check questionnaire to the user's device and collects the results. The AI ​​analyzes the questionnaire responses and suggests relaxation methods and stress reduction measures as needed.

[1040] 7. Community Recommendations

[1041] The server recommends suitable online communities based on the user's profile, and the user can join the recommended communities and share information and experiences with other members.

[1042] 8. Photo analysis and album generation

[1043] Users upload ultrasound images and photos of their child's growth record to their device, and the server uses facial recognition technology to analyze the images, selects important photos, and automatically creates a digital album.

[1044] 9. Product Recommendations and In-Store Navigation

[1045] Based on the user's profile information, the app recommends appropriate products, such as nutritional supplements and toys suited to the developmental stage of a child or expectant mother. It also displays the location of the recommended products in the store and provides the shortest route, allowing users to find the products efficiently.

[1046] Hardware and software used

[1047] Hardware: Smartphone

[1048] Software: Python, React Native as frontend, MySQL as database

[1049] AI Technology: Generative AI Models that Use Natural Language Processing (NLP)

[1050] Specific examples

[1051] Let's say a user is 20 weeks pregnant and shopping in a brick-and-mortar store. The user opens the in-store app on their smartphone.

[1052] 1. Collection of User Data

[1053] The user enters profile information (age, number of weeks pregnant, health status, etc.) and submits it.

[1054] 2. Providing personalized advice

[1055] When a user asks, "What can I do to combat morning sickness?", the AI ​​will provide personalized advice such as, "Diets containing ginger are effective."

[1056] 3. Health data management and monitoring

[1057] When a user enters their weight, if it is determined that their weight is increasing rapidly, the server will send a warning.

[1058] 4. Product Recommendations and In-Store Navigation

[1059] The system suggests recommended products such as folic acid supplements (A3) and vitamin D supplements (A5) and displays the shortest route within the store.

[1060] Prompt Sentence Examples

[1061] "For a user who is 20 weeks pregnant, please recommend the best products to purchase in a physical store and suggest a route, including specific shelf locations."

[1062] This allows users to shop comfortably and efficiently, while also providing support tailored to individual needs.

[1063] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1064] Step 1:

[1065] User Data Collection:

[1066] The user enters their profile information (age, number of weeks pregnant, health condition, past medical history, age of child, etc.) into the terminal. This input data is sent from the terminal to the server, and the server stores the received data in a database. The input here is the user's profile information, and the output is the user data stored on the server.

[1067] Step 2:

[1068] Information generation:

[1069] The server periodically collects data from external medical databases and research papers and stores it in an internal database. It uses AI technology (generative AI models) to generate up-to-date information on pregnancy, childbirth, and parenting. The input is external medical data and research papers, and the output is the generated up-to-date information.

[1070] Step 3:

[1071] Information distribution:

[1072] The server sends the generated information to the user's device, where the user can view the information through an application or web interface. The input is the generated information, and the output is the delivery of the information to the user's device.

[1073] Step 4:

[1074] Personalized advice provided:

[1075] When a user enters a specific question into the device, the question is sent to the server, where the AI ​​generates personalized advice based on the user's profile information and the question, and sends the answer to the device. The input is the user's question and profile information, and the output is personalized advice.

[1076] Step 5:

[1077] Health data management and monitoring:

[1078] Users enter their own and their children's health information (weight, body temperature, dietary details, etc.) into the device. The device sends this data to a server, which uses AI to analyze the data and monitor the health status. If any abnormalities are detected as a result of this analysis, a warning is sent. The input is the user's health data, and the output is the analysis results and a warning in the event of an abnormality.

[1079] Step 6:

[1080] Mental health support:

[1081] The server periodically sends a stress check questionnaire to the user's device and collects the results. The AI ​​analyzes the questionnaire responses and suggests relaxation methods and stress reduction measures as needed. The input is the questionnaire response data, and the output is the analysis results and suggested relaxation methods.

[1082] Step 7:

[1083] Community Recommendations:

[1084] The server recommends appropriate online communities based on the user's profile information. The user can join the recommended communities and share information and experiences with other members. The input is the user's profile information, and the output is the recommended community information.

[1085] Step 8:

[1086] Photo analysis and album generation:

[1087] Users upload ultrasound images and photos recording their child's growth to their device. The server analyzes the images using facial recognition technology and selects important photos. A digital album is automatically generated based on the selected photos. The input is the photo data uploaded by the user, and the output is the analysis results and the generated digital album.

[1088] Step 9:

[1089] Product recommendations and in-store navigation:

[1090] The server recommends appropriate products based on the user's profile information. The location information of the recommended products is compared with the store map to calculate the optimal route. The user can check the recommended products and their locations, as well as the shortest route within the store, through their device. The input is the user's profile information, store map information, and product data, and the output is recommended product information and the store route.

[1091] 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.

[1092] This invention combines an emotion engine with a comprehensive support system for pregnancy, childbirth, and child-rearing to recognize the user's emotions and provide more accurate, personalized support. The system uses AI technology to collect user data and provides personalized information and advice based on that data. In particular, the invention aims to utilize the user's emotion data to more accurately understand the user's mental health and overall well-being and provide appropriate support tailored to the user's needs.

[1093] Overview of program processing

[1094] 1. How we collect user data

[1095] Users enter their profile information into the device, including their age, pregnancy status, health status, and past medical history.

[1096] The terminal sends this information to the server, which stores it in a database.

[1097] 2. Information generation means

[1098] The server periodically collects data from external medical databases and the latest research papers and stores it in an internal database.

[1099] The AI ​​uses the collected data to generate up-to-date information on pregnancy, childbirth, and parenting, which is then presented through an interface for users to access.

[1100] 3. Information distribution methods

[1101] The server distributes the generated information through a user interface (app or website).

[1102] Users can access this information through an app or web interface.

[1103] 4. Means of personalized advice delivery

[1104] A user enters a specific question into the terminal, which then transmits the question to the server.

[1105] The server uses AI to generate personalized advice based on the user's profile information and questions, and sends the answer to the device.

[1106] Examples:

[1107] When a user asks, "What can I do to combat morning sickness?", the AI ​​will refer to other data that matches the user's profile (for example, the number of weeks pregnant) and provide specific measures, such as "Diets containing ginger are effective."

[1108] 5. Health data management and monitoring measures

[1109] Users enter their own and their children's health information (weight, body temperature, dietary details, etc.) into the device.

[1110] The device sends this data to a server, which then uses AI to analyze the data and monitor the user's health.

[1111] Examples:

[1112] Users enter their daily weight, and the server analyzes the data and sends alerts if their weight is increasing too rapidly.

[1113] 6. Mental health support measures

[1114] The server periodically sends a stress check questionnaire to the user's device and collects the results.

[1115] The AI ​​will analyze the survey responses and suggest relaxation and stress reduction methods as needed.

[1116] Examples:

[1117] If the user answers the questionnaire indicating high stress, the server will suggest "relaxation breathing techniques."

[1118] 7. Community Recommendations

[1119] The server recommends appropriate online communities based on the user's profile.

[1120] Users can join recommended communities and share information and experiences with other members.

[1121] Examples:

[1122] New moms are encouraged to join the "First Time Parenting Community" where they can share information and experiences with other new moms.

[1123] 8. Photo analysis and album generation method

[1124] Users upload ultrasound images and photos of their child's growth record to the device.

[1125] The server uses facial recognition technology to analyze the photos and select the most important ones.

[1126] A digital album is automatically generated based on the selected photos.

[1127] Examples:

[1128] When users upload one ultrasound photo per month, the server organizes them in chronological order and creates a growth record album.

[1129] Combining Emotion Engines

[1130] 9. Emotion Recognition with Emotion Engine

[1131] Users can input their daily moods and emotions through the device, and emotions can also be recognized through voice input and facial expression capture.

[1132] The device sends this emotional data to the server, which then analyzes it using an emotion engine.

[1133] Examples:

[1134] When a user uses the diary function and enters "I'm very tired today," the emotion engine understands "tired" and the server stores that data.

[1135] 10. Personalized advice based on emotional data

[1136] The server adjusts the content and tone of the advice based on the user's emotional data recognized by the emotion engine. For example, if the user is feeling stressed, the server will provide encouraging advice in a gentle tone.

[1137] Users can receive more personalized advice through their devices.

[1138] Examples:

[1139] If the user types "I'm frustrated," the server will offer gentle advice like "Try to relax a bit today."

[1140] 11. Strengthening mental health support

[1141] The emotion engine combines the results of traditional stress tests with emotional data to provide a more accurate mental health assessment.

[1142] Based on this, the server provides more appropriate relaxation methods and necessary support.

[1143] Examples:

[1144] If the user shows high stress in the stress check and the emotional data indicates "anxiety," the server will not only provide "deep breathing and meditation" methods but also recommend "booking a counseling appointment."

[1145] Through the above components and processes, this system comprehensively provides the information and support needed at each stage of pregnancy, childbirth, and child-rearing. This allows each user to not only obtain the information that is most suited to them, but also receive psychological support tailored to their emotions. Furthermore, by sharing information with other users in the same situation through the community function, users can receive even more comprehensive support.

[1146] The processing flow will be explained below.

[1147] 1. Generating information about pregnancy, childbirth, and child-rearing

[1148] Step 1:

[1149] The server periodically collects data from external medical databases and the latest research papers.

[1150] Specific operation: The server retrieves information from medical journals and databases via API and stores it in an internal database.

[1151] Step 2:

[1152] The server inputs the collected data into AI to generate information about pregnancy, childbirth, and child-rearing.

[1153] Specific operation: The AI ​​analyzes the collected data and uses a natural language generation algorithm to create sentences that are easy for users to understand.

[1154] Step 3:

[1155] The server distributes the generated information through a user interface (app or website).

[1156] Specific operation: The generated articles and information pages are uploaded to a web server so that users can access them.

[1157] 2. Providing personalized advice to users

[1158] Step 1:

[1159] Users enter their profile information into the device (e.g., age, number of weeks pregnant, health status).

[1160] Specific operation: The device displays a profile entry form, and once the profile entry is complete, it sends the data to the server.

[1161] Step 2:

[1162] The user inputs a specific question into the terminal.

[1163] Specific operation: The terminal displays a question form, and when the user enters a question and presses the send button, the question data is sent to the server.

[1164] Step 3:

[1165] The server inputs the user's profile information and questions into the AI ​​to generate personalized advice.

[1166] What it does: The AI ​​searches the database and creates personalized advice based on relevant information.

[1167] Step 4:

[1168] The server transmits the generated advice to the user terminal.

[1169] Specific operation: The created answer is delivered to the device in real time.

[1170] 3. Health care for mothers and children

[1171] Step 1:

[1172] Users input their daily health data (weight, body temperature, dietary content, etc.) into the device.

[1173] Specific operation: The terminal provides an input interface, and after data is entered, the data is sent to the server by pressing the send button.

[1174] Step 2:

[1175] The terminal transmits the input data to the server.

[1176] Specific operation: The device sends data to the server via an HTTP request or API.

[1177] Step 3:

[1178] The server analyzes the received data using AI and monitors the health status.

[1179] What it does: The AI ​​analyzes the data, checks for any anomalies, and runs algorithms to assess whether it's within the normal range.

[1180] Step 4:

[1181] The server generates feedback for the user based on the analysis results and sends it to the device.

[1182] Specific operation: Analysis results and recommended actions are sent to the device in real time.

[1183] 4. Mental health support

[1184] Step 1:

[1185] The server periodically sends a stress check questionnaire to the terminal.

[1186] Specific operation: The server generates a stress check form and sends it to the terminal based on the specified schedule.

[1187] Step 2:

[1188] The user answers the questionnaire and enters it into the terminal.

[1189] Specific operation: The terminal provides an interface for answering the survey questions, and after entering the answer, displays a submit button.

[1190] Step 3:

[1191] The terminal sends the questionnaire responses to the server.

[1192] Specific operation: The device sends the response data to the server via an HTTP request or API.

[1193] Step 4:

[1194] The server analyzes the response data using AI and evaluates stress levels.

[1195] What it does: The AI ​​analyzes your answers and runs an algorithm to quantify your stress level.

[1196] Step 5:

[1197] Based on the analysis results, the server suggests relaxation methods and sends them to the device.

[1198] Specific operation: Generate proposal content and send it to the terminal.

[1199] 5. Community Recommendations

[1200] Step 1:

[1201] The server recommends appropriate communities based on the user's profile.

[1202] Specific Operation: The server parses the profile information and generates a list of appropriate communities.

[1203] Step 2:

[1204] Users join recommended communities.

[1205] Specific operation: The terminal provides a participation interface and displays a participation button.

[1206] Step 3:

[1207] Users share information and experiences within the community.

[1208] Specific operation: The device provides messaging and posting functions to share information with other users.

[1209] 6. Memories storage

[1210] Step 1:

[1211] Users upload ultrasound images and photos of their child's growth record to the device.

[1212] Specific operation: The terminal provides a photo upload interface and sends the uploaded photo data to the server.

[1213] Step 2:

[1214] The server analyzes the uploaded photos using facial recognition technology.

[1215] How it works: The AI ​​analyzes the photo data and runs an algorithm to identify important people in the photos.

[1216] Step 3:

[1217] The server selects important photos and generates an automatic album.

[1218] Specific operation: Organize photos chronologically and generate a digital album layout for the user.

[1219] Step 4:

[1220] The server transmits the generated album to the terminal.

[1221] Specific Actions: Create a digital album and provide a link for users to access it.

[1222] 7. Emotion Recognition with Emotion Engine

[1223] Step 1:

[1224] Users can input their moods and emotions into the device, and voice input and facial recognition are also available for facial expression capture.

[1225] Specific operation: The device provides an emotion input interface and collects voice and facial expression data.

[1226] Step 2:

[1227] The terminal transmits the emotion data to the server.

[1228] Specific operation: Sends voice and facial expression data to the server via HTTP request or API.

[1229] Step 3:

[1230] The server uses an emotion engine to analyze the transmitted emotion data.

[1231] Specific operation: Analyzes data using emotion recognition algorithms to determine the user's emotional state.

[1232] 8. Personalized advice based on emotional data

[1233] Step 1:

[1234] The server adjusts the content and tone of the advice based on the emotional data recognized by the emotion engine.

[1235] Specific operation: The newly acquired emotion data is applied to the advice generation algorithm to generate appropriate advice.

[1236] Step 2:

[1237] The server transmits the generated advice to the user terminal.

[1238] Specific operation: Advice content is delivered to the device in real time.

[1239] 9. Strengthening mental health support

[1240] Step 1:

[1241] The emotion engine integrates stress check results with emotional data to provide a more accurate mental health assessment.

[1242] How it works: An analytical algorithm combines stress levels and emotional data to assess your overall mental health.

[1243] Step 2:

[1244] Based on the overall evaluation results, the server will suggest further appropriate relaxation methods and support.

[1245] Specific operation: Generate proposal content and send it to the terminal.

[1246] Through the above processing steps, information and support related to pregnancy, childbirth, and child-rearing are provided to users. By utilizing the emotion engine, the system effectively supports the user's mental health and provides personalized information and advice according to their physical condition and emotions.

[1247] Example 2

[1248] 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."

[1249] Conventional information systems related to pregnancy, childbirth, and child-rearing have struggled to provide information and advice tailored to each user's individual circumstances and emotions. Furthermore, methods for comprehensively supporting users' mental health have been limited. Furthermore, there is a need for a comprehensive system that can provide a wide range of support, including photo management and community recommendation functions.

[1250] 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.

[1251] In this invention, the server includes means for collecting user data, means for generating information about pregnancy, childbirth, and child-rearing based on the collected data, means for distributing the generated information to users, means for generating and providing personalized advice based on user questions, means for collecting, analyzing, and monitoring individual health information, means for analyzing emotional data and suggesting relaxation methods as needed to support the user's mental health, means for recommending communities and sharing information among users, means for analyzing uploaded image data, selecting appropriate photos, and generating albums, means for collecting and analyzing user emotional data using an emotion engine, and means for providing personalized advice based on the analyzed emotional data. This allows users to receive information and support optimized for their own situation and emotions.

[1252] "User data" refers to information about system users, including profile information, health status, number of weeks pregnant, and past medical history.

[1253] "Means for collecting" refers to a method or device for having a user input data, transmitting it from the terminal to a server, and storing it in a database.

[1254] "Means for generating information" refers to methods and devices that use AI or servers to create useful information about pregnancy, childbirth, and child-rearing based on collected data.

[1255] The "means for distributing" refers to a method or device for distributing the generated information to a user's terminal.

[1256] "Personalized advice" refers to advice or suggestions that are tailored to a user's specific situation based on their individual information.

[1257] "Means for collecting, analyzing, and monitoring health information" refers to methods and devices that collect and analyze data related to the health of users and their children, and monitor the results regularly.

[1258] "Means for suggesting relaxation methods to support mental health" refers to a method or device that analyzes the user's emotions and stress state and suggests appropriate relaxation methods or stress reduction measures based on the results.

[1259] "Means for recommending communities and sharing information" refers to a method or device for recommending appropriate online communities based on user profile data and supporting information exchange among users within those communities.

[1260] "Means for analyzing image data and generating an album" refers to a method or device that analyzes photos and image data uploaded by users, selects important images, and automatically generates a digital album.

[1261] An "emotion engine" refers to software or algorithms that recognize and analyze emotions from user input data, voice, facial expression data, etc.

[1262] This invention combines an emotion engine with a comprehensive support system for pregnancy, childbirth, and child-rearing to recognize the user's emotions and provide more accurate, personalized support. The system uses AI technology to collect user data and provides personalized information and advice based on that data. In particular, the invention aims to utilize the user's emotion data to more accurately understand the user's mental health and overall well-being and provide appropriate support tailored to the user's needs.

[1263] How user data is collected

[1264] The user enters their profile information into the device, such as their age, number of weeks pregnant, health status, and past medical history.

[1265] The terminal sends this information to a server, which stores it in a database. The software used here is a database management system (DBMS).

[1266] Information generation means

[1267] The server periodically collects data from external medical databases and the latest research papers and stores it in an internal database.

[1268] The AI ​​uses the collected data to generate up-to-date information about pregnancy, childbirth, and parenting, which is then presented through a user interface. The software used is an AI model equipped with natural language processing (NLP) algorithms.

[1269] Information distribution method

[1270] The server distributes the generated information through a user interface (app or website).

[1271] Users can access this information through an app or web interface. The software used here is a web application framework and a mobile application platform.

[1272] Personalized advice delivery methods

[1273] A user enters a specific question into the terminal, which then transmits the question to the server.

[1274] The server uses AI to generate personalized advice based on the user's profile information and questions, and sends the answer to the device.

[1275] Examples:

[1276] When a user asks, "What can I do to combat morning sickness?", the AI ​​will refer to other data that matches the user's profile (e.g., number of weeks pregnant) and provide specific measures such as "Diets containing ginger are effective." An example of a prompt sentence in this case is, "What can I do to combat morning sickness?"

[1277] Health data management and monitoring tools

[1278] Users enter their own and their children's health information (weight, body temperature, dietary details, etc.) into the device.

[1279] The device sends this data to a server, which then uses AI to analyze the data and monitor the user's health.

[1280] Examples:

[1281] When a user enters their daily weight, the server analyzes the data and sends a warning if their weight is increasing rapidly. An example of a prompt sentence is "Your weight today is 80 kg."

[1282] Mental health support measures

[1283] The server periodically sends a stress check questionnaire to the user's device and collects the results.

[1284] The AI ​​will analyze the survey responses and suggest relaxation and stress reduction methods as needed.

[1285] Examples:

[1286] If the user answers the questionnaire indicating high stress, the server will suggest "breathing exercises for relaxation." An example of a prompt is "How often have you felt stressed recently?"

[1287] Community Recommendations

[1288] The server recommends appropriate online communities based on the user's profile.

[1289] Users can join recommended communities and share information and experiences with other members.

[1290] Examples:

[1291] New moms are encouraged to join a "first-time parenting community" where they can share information and experiences with other new moms. An example of a prompt is "Do you want to make mommy friends?"

[1292] Photo analysis and album generation tool

[1293] Users upload ultrasound images and photos of their child's growth record to the device.

[1294] The server uses facial recognition technology to analyze the photos and select the most important ones.

[1295] A digital album is automatically generated based on the selected photos.

[1296] Examples:

[1297] When a user uploads one ultrasound photo per month, the server organizes them in chronological order and creates a growth record album. An example of a prompt is "Please upload this month's ultrasound photo."

[1298] Combining Emotion Engines

[1299] Emotion recognition by emotion engine

[1300] Users can input their daily moods and emotions through the device, and emotions can also be recognized through voice input and facial expression capture.

[1301] The device sends this emotional data to the server, which then analyzes it using an emotion engine.

[1302] Examples:

[1303] When a user uses the diary function and enters "I'm very tired today," the emotion engine understands "tired" and the server stores the data. An example of a prompt sentence is "Please tell me how you feel today."

[1304] Personalized advice based on emotional data

[1305] The server adjusts the content and tone of the advice based on the user's emotional data recognized by the emotion engine. For example, if the user is feeling stressed, the server will provide encouraging advice in a gentle tone.

[1306] Users can receive more personalized advice through their devices.

[1307] Examples:

[1308] If the user types "I'm frustrated," the server might offer gentle advice such as "Try to relax a bit today." An example of a prompt sentence is "I'm frustrated, what should I do?"

[1309] Strengthening mental health support

[1310] The emotion engine combines the results of traditional stress tests with emotional data to provide a more accurate mental health assessment.

[1311] Based on this, the server provides more appropriate relaxation methods and necessary support.

[1312] Examples:

[1313] If the user's stress check indicates high stress and the emotional data indicates "anxiety," the server will not only provide "deep breathing and meditation" methods but also recommend "booking a counseling appointment." An example of a prompt sentence is, "I've been feeling a lot of anxiety lately. What should I do?"

[1314] Through the above components and processes, this system comprehensively provides the information and support needed at each stage of pregnancy, childbirth, and child-rearing. This allows each user to not only obtain the information that is most suited to them, but also receive psychological support tailored to their emotions. Furthermore, by sharing information with other users in the same situation through the community function, users can receive even more comprehensive support.

[1315] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1316] Step 1: Enter and submit user data

[1317] The user enters their profile information into the device, such as age, pregnancy status, health status, and past medical history.

[1318] Input: User profile information

[1319] The terminal sends the entered information to the server. Specifically, when data is entered through a form and the send button is pressed, the data is sent to the server in real time.

[1320] Output: User data sent to the server

[1321] Specific operation: The user enters information into the profile entry screen of the app and presses the send button. The device then sends the data to the server.

[1322] Step 2: Save user data

[1323] The server receives the user data sent from the terminal and stores it in a database using a database management system (DBMS).

[1324] Input: User data sent from the terminal

[1325] Output: User data stored in the database

[1326] Specific operation: The server uses the database API to retrieve the received data and save it in the database.

[1327] Step 3: Collect medical data

[1328] The server collects data from external medical databases and the latest research papers and stores it in an internal database.

[1329] Input: External medical databases and research papers

[1330] Output: Medical data stored in an internal database

[1331] Specific operation: The server periodically collects medical data using an external API and stores it in its own database.

[1332] Step 4: Information Generation

[1333] The AI ​​built into the server generates the latest information on pregnancy, childbirth, and child-rearing based on user and medical data.

[1334] Input: User data, medical data

[1335] Output: Latest information generated

[1336] How it works: The AI ​​model analyzes the user's profile information and the latest medical data to generate information appropriate for the user.

[1337] Step 5: Distributing information

[1338] The server delivers the generated information to the user through a user interface (app or website).

[1339] Input: Latest generated information

[1340] Output: Information delivered to the user

[1341] Specific behavior: The server generates information and sends it to a user interface using an API to display it on the app's home screen or website dashboard.

[1342] Step 6: Enter and submit your specific question

[1343] The user types a specific question into the device, such as "Please tell me what to do about morning sickness."

[1344] Input: User's specific question

[1345] The terminal sends a query to the server.

[1346] Output: The query data sent to the server

[1347] Specific operation: The user enters a specific question into the question input field of the app and presses the send button. The device then sends the question data to the server.

[1348] Step 7: Generate personalized advice

[1349] The server uses AI to generate personalized advice based on the user's profile information and questions.

[1350] Input: User profile information, specific questions

[1351] Output: Generated personalized advice

[1352] How it works: The AI ​​model references the user's profile and question to generate the most appropriate advice.

[1353] Step 8: Distributing Advice

[1354] The server transmits the generated advice to the terminal.

[1355] Input: Generated personalized advice

[1356] Output: Advice delivered to the terminal

[1357] Specific operation: The server uses an API to send the generated advice data to the terminal and notifies the user's terminal.

[1358] Step 9: Enter and submit your health information

[1359] Users enter their own and their children's health information into the device, such as weight, body temperature, and dietary details.

[1360] Input: Health information

[1361] The terminal transmits this data to the server.

[1362] Output: Health data sent to the server

[1363] Specific operation: The user enters health information into the app and presses the send button. The device then sends the data to the server.

[1364] Step 10: Health data storage and analysis

[1365] The server stores the submitted health data in a database and analyzes it using AI.

[1366] Input: Health data

[1367] Output: Analyzed health data

[1368] How it works: The server receives health data and stores it in a database. The AI ​​model analyzes the data and monitors for abnormalities.

[1369] Step 11: Submit the stress check questionnaire

[1370] The server periodically sends a stress check questionnaire to the user's terminal.

[1371] Input: Stress check questionnaire

[1372] Output: Survey sent to user's device

[1373] Specific operation: The server uses an API to send stress check questionnaire data to the terminal and submits questionnaires to the user at high frequency.

[1374] Step 12: Complete and submit the survey

[1375] The user answers the stress check questionnaire.

[1376] Input: Stress check questionnaire response

[1377] The terminal sends the response to the server.

[1378] Output: Survey responses sent to the server

[1379] Specific operation: The user answers the questionnaire and presses the send button. The device sends the answer data to the server.

[1380] Step 13: Analyze stress data and propose relaxation methods

[1381] The server uses AI to analyze the questionnaire responses and suggest relaxation methods as needed.

[1382] Input: Survey response data

[1383] Output: Proposed relaxation method

[1384] Specific operation: The AI ​​model analyzes stress data, devises stress reduction measures, and suggests them to the user.

[1385] Step 14: Community Recommendations

[1386] The server recommends appropriate online communities based on the user's profile.

[1387] Input: User profile information

[1388] Output: Community recommendations

[1389] Specific operation: The server analyzes the profile information and generates a list of recommended communities.

[1390] Step 15: Upload and analyze photos

[1391] Users upload ultrasound images and photos of their child's growth record to the device.

[1392] Input: Ultrasound photos and growth record photos

[1393] The device sends the photo to the server.

[1394] Output: Photo data sent to the server

[1395] Specific operation: The user uploads a photo in the specified location in the app, and the device sends it to the server.

[1396] Step 16: Create an album

[1397] The server uses facial recognition technology to analyze the photos, select important photos, and generate a digital album.

[1398] Input: Photo data

[1399] Output: Digital album

[1400] Specific operation: The server analyzes the photo data, organizes it chronologically, and generates a growth record album.

[1401] Step 17: Enter and send emotion data

[1402] The user inputs emotions into the device, including voice input and facial expression capture.

[1403] Input: Emotion data

[1404] The terminal transmits the emotion data to the server.

[1405] Output: Emotion data sent to the server

[1406] Specific operation: The user inputs data expressing emotions into the terminal, and the terminal transmits the data to the server.

[1407] Step 18: Analyze and store emotion data

[1408] The server uses an emotion engine to analyze the emotion data and saves the results.

[1409] Input: Emotion data

[1410] Output: Parsed emotion data

[1411] Specific operation: The emotion engine analyzes the emotion data and stores it in the server's database.

[1412] Step 19: Generating personalized advice based on sentiment data

[1413] The server adjusts the content and tone of the advice based on the emotional data recognized by the emotion engine.

[1414] Input: Parsed emotion data

[1415] Output: Adjusted advice

[1416] Specific operation: The AI ​​generates advice that reflects emotional data and provides it in a form appropriate for the user.

[1417] Step 20: Providing personalized advice

[1418] The server delivers the tailored advice to the user's terminal.

[1419] Input: Tailored Advice

[1420] Output: Advice delivered to the user's device

[1421] Specific operation: The server sends the generated advice data to the device so that the user can view it in the app.

[1422] In this way, the system provides comprehensive and personalized support to users while performing a wide range of data collection, analysis, information generation and distribution.

[1423] (Application example 2)

[1424] 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."

[1425] Support systems for pregnancy, childbirth, and child-rearing are required to accurately grasp the emotional state and health information of individual users and provide appropriate advice and support in real time. However, conventional systems have difficulty responding to emotional changes in a personalized manner, and have not been able to provide sufficient satisfaction to users. Furthermore, to improve the quality of advice in physical stores, flexible responses according to the customer's emotional state are necessary.

[1426] 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 user data, means for generating information about pregnancy, childbirth, and child-rearing based on the collected data, means for distributing the generated information to the user, means for generating and providing personalized advice based on the user's questions, means for managing, analyzing, and monitoring health data of the mother and child, means for conducting and analyzing stress checks to support the user's mental health and suggesting appropriate relaxation methods, means for recommending communities and allowing users to share information, means for analyzing uploaded photos, selecting appropriate photos, and generating albums, means for analyzing the user's emotional state based on emotional data and adjusting the content and tone of personalized advice, and means for recognizing customer emotions in real time at a physical store and providing individual counseling and advice tailored to the situation. This allows users to receive personalized advice and support in real time based on their emotions and health condition.

[1427] "User Data" is a set of data about a user, such as the user's profile information, health information, and emotional state.

[1428] A "means for collecting" is a method or device for inputting, obtaining, or detecting user data.

[1429] The "means for generating information" refers to a method or device for generating information related to pregnancy, childbirth, and child-rearing based on collected user data.

[1430] "Means for distributing information" refers to a method or device for providing the generated information to users.

[1431] "Personalized advice" is advice that is specifically tailored to a user's question or situation.

[1432] "Health data" refers to data such as the weight, temperature, and health status of the mother and child.

[1433] "Management, analysis and monitoring means" refers to a set of methods or devices for collecting health data, analyzing and monitoring it, and providing appropriate support to users.

[1434] A "stress check" is a questionnaire or assessment conducted to assess a user's mental health.

[1435] "Relaxation techniques" refer to breathing techniques, meditation, relaxation techniques, etc. that are used to reduce mental stress.

[1436] A "community" is a group or online forum where users with a common interest share information and experiences.

[1437] The "means for analyzing photos and generating an album" refers to a method or device for analyzing uploaded photos, selecting important images, and creating a digital album.

[1438] "Emotion data" is data that indicates the user's daily mood and emotional state.

[1439] The "means for analyzing emotional state" refers to a method or device for recognizing and evaluating the user's emotions based on emotional data.

[1440] A "brick and mortar store" is a physical store where customers receive goods or services in person.

[1441] A "means for recognizing customer emotions in real time" is a method or device that can instantly grasp a customer's current emotions.

[1442] "Means for providing counseling and advice" refers to a method or device that provides appropriate support in response to the user's feelings and questions.

[1443] This invention is a comprehensive support system for pregnancy, childbirth, and child-rearing, which recognizes the user's emotions by combining an emotion engine and provides more accurate and personalized support. An embodiment of this system will be described in detail below.

[1444] Hardware and software used

[1445] Hardware: smartphones, tablets, back-end servers

[1446] Software: Emotion recognition engine, AI model (e.g., TensorFlow, GPT-3), database (e.g., MySQL, Firebase), user interface (e.g., Vue.js, React Native)

[1447] System Program

[1448] First, user data is collected, where users enter their profile information, health information, and daily emotional state using a smartphone or tablet device, and this data is sent in real time to a back-end server and stored in a database.

[1449] Next, AI generates information about pregnancy, childbirth, and child-rearing based on the collected data. It compares and analyzes user data stored in the database with data collected from external medical databases and the latest research papers. This generates the most up-to-date and accurate information and provides it to users.

[1450] The generated information is delivered to the user through an interface. When a user enters a question through an app or tablet, the question is sent to the server. The server uses AI to generate personalized advice based on the question and the user's profile information and sends it back to the device.

[1451] The user data also includes health data of the mother and child, which is managed, analyzed, and monitored by the server. If any abnormalities are found in the health data, warnings and countermeasures are automatically proposed.

[1452] Supporting mental health is also an important element. The server periodically sends users stress check questionnaires and analyzes their responses. The emotion engine recognizes the user's emotional state and then personalized suggestions are made for relaxation and stress reduction.

[1453] The system also has a photo analysis and album generation function. Ultrasound photos and growth record photos uploaded by users are analyzed using AI, and important photos are automatically selected and created as a digital album.

[1454] Finally, we will explain how this system can be applied to physical stores. When customers visit a physical store, they can input their emotional state on the spot using a smartphone or tablet, or their emotional state can be analyzed in real time by an emotion recognition engine. This information is immediately sent to a server, which then provides appropriate counseling or advice.

[1455] Examples of concrete examples and prompts

[1456] For example, if a customer visiting a physical store types in "I feel irritated while breastfeeding," the emotion engine will recognize the word "irritation," and the AI ​​model will suggest "simple breathing exercises to help you relax" based on profile data such as the number of weeks pregnant and health status. It will also recommend places to purchase relaxation products and nearby mental health support organizations.

[1457] Prompt Sentence Examples

[1458] Ask the AI ​​model the following prompt:

[1459] User profile data: Age: "30", Pregnancy week: "20 weeks", Health status: "Normal"

[1460] Emotional data: "I'm feeling very frustrated today."

[1461] Q: "What can I do to reduce frustration while breastfeeding?"

[1462] Answer: "Try some breathing exercises to help you relax, especially taking deep breaths. Also, consider using relaxation aids."

[1463] In this way, the embodiments of the invention can provide personalized advice and support in real time according to the user's emotions and health condition.

[1464] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1465] Step 1:

[1466] A user uses a smartphone or tablet device to input their profile information, health information, and daily emotional state. This includes age, pregnancy week, health condition, and emotion (e.g., "I'm irritated"). The input data is sent from the device to a server in real time. The server receives this data and stores it in a database. Here, the input is the user's profile information and emotional data, and the output is the user data stored in the database.

[1467] Step 2:

[1468] The server generates information about pregnancy, childbirth, and child-rearing based on user data stored in the database and data collected from external medical databases and the latest research papers. An AI model (e.g., TensorFlow or GPT-3) processes this information and generates up-to-date and accurate information. The input is user data and external data, and the output is the generated up-to-date information.

[1469] Step 3:

[1470] The server delivers the generated information to the user, who then displays it on their smartphone or tablet through a user interface (e.g., Vue.js, React Native). The input is the generated up-to-date information, and the output is the information displayed in the user interface.

[1471] Step 4:

[1472] The user inputs a specific question via an app or tablet. For example, "What can I do if I get irritated while breastfeeding?" The input question is sent from the device to the server. The server uses an AI model to generate personalized advice based on the question and the user's profile information, and sends it back to the device. The input is the user's question and profile information, and the output is personalized advice.

[1473] Step 5:

[1474] The health data of the user's mother and child is managed, analyzed, and monitored by a server. The user enters health data (e.g., weight, temperature) into the device and sends it to the server. The server analyzes this data using AI, and if any abnormalities are detected, it automatically issues warnings and suggests countermeasures. The input is health data, and the output is the analysis results and countermeasures.

[1475] Step 6:

[1476] The server periodically sends a stress check questionnaire to the user's device. The user answers the questionnaire and the data is sent to the server. The server uses an emotion recognition engine to analyze the user's emotional state and suggests relaxation methods and stress reduction measures. The input is the questionnaire response data and emotional data, and the output is the suggested relaxation methods.

[1477] Step 7:

[1478] The server recommends suitable online communities to users through the community function. It selects and recommends relevant communities based on the user's profile information. The input is the user's profile information, and the output is the recommended communities.

[1479] Step 8:

[1480] Users upload ultrasound images and growth record photos to their device. The server uses AI to analyze them, selects important photos, and generates a digital album. The input is the uploaded photos, and the output is the generated digital album.

[1481] Step 9:

[1482] In physical stores, customers input their emotional state using a smartphone or tablet, and the device's emotion recognition engine analyzes their emotional state in real time. The information is immediately sent to the server, which then provides appropriate counseling and advice. The input is the emotional data of the physical store customer, and the output is real-time counseling and advice.

[1483] 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.

[1484] 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.

[1485] 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.

[1486] [Third embodiment]

[1487] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1488] 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.

[1489] 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).

[1490] 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.

[1491] 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.

[1492] 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).

[1493] 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.

[1494] 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.

[1495] 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.

[1496] 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.

[1497] 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.

[1498] 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."

[1499] This invention is a system that provides a series of information and support related to pregnancy, childbirth, and child-rearing, and its core is information generation and personalization using AI technology. The components of this system consist of various means for collecting user data and providing information and advice generated based on that data.

[1500] Overview of program processing

[1501] 1. How we collect user data

[1502] Users first enter their profile information into the device, including their age, number of weeks pregnant, health status, and past medical history.

[1503] The terminal sends this information to the server, which stores it in a database.

[1504] 2. Information generation means

[1505] The server periodically collects data from external medical databases and the latest research papers and stores it in an internal database.

[1506] The AI ​​uses the collected data to generate up-to-date information on pregnancy, childbirth, and parenting, which is then presented through an interface for users to access.

[1507] 3. Information distribution methods

[1508] The server sends the generated information to the device for viewing by the user, who can access this information through an app or web interface.

[1509] 4. Means of personalized advice delivery

[1510] A user enters a specific question into the terminal, which then transmits the question to the server.

[1511] The server uses AI to generate personalized advice based on the user's profile information and questions, and sends the answer to the device.

[1512] Examples:

[1513] When a user asks, "What can I do to combat morning sickness?", the AI ​​will refer to other data that matches the user's profile (for example, the number of weeks pregnant) and provide specific measures, such as "Diets containing ginger are effective."

[1514] 5. Health data management and monitoring measures

[1515] Users enter their own and their children's health information (weight, body temperature, dietary details, etc.) into the device.

[1516] The device sends this data to a server, which then uses AI to analyze the data and monitor the user's health.

[1517] Examples:

[1518] Users enter their daily weight, and the server analyzes the data and sends alerts if their weight is increasing too rapidly.

[1519] 6. Mental health support measures

[1520] The server periodically sends a stress check questionnaire to the user's device and collects the results.

[1521] The AI ​​will analyze the survey responses and suggest relaxation and stress reduction methods as needed.

[1522] Examples:

[1523] If the user answers the questionnaire indicating high stress, the server will suggest "relaxation breathing techniques."

[1524] 7. Community Recommendations

[1525] The server recommends appropriate online communities based on the user's profile.

[1526] Users can join recommended communities and share information and experiences with other members.

[1527] Examples:

[1528] New moms are encouraged to join the "First Time Parenting Community" where they can share information and experiences with other new moms.

[1529] 8. Photo analysis and album generation method

[1530] Users upload ultrasound images and photos of their child's growth record to the device.

[1531] The server uses facial recognition technology to analyze the photos and select the most important ones.

[1532] A digital album is automatically generated based on the selected photos.

[1533] Examples:

[1534] When users upload one ultrasound photo per month, the server organizes them in chronological order and creates a growth record album.

[1535] Through the above components and processes, this system comprehensively provides the information and support needed at each stage of pregnancy, childbirth, and child-rearing. This allows each user to not only obtain the information that is most suitable for them, but also receive psychological support. Furthermore, by sharing information with other users in the same situation through the community function, users can receive even more comprehensive support.

[1536] The processing flow will be explained below.

[1537] 1. Generating information about pregnancy, childbirth, and child-rearing

[1538] Step 1:

[1539] The server periodically collects data from external medical databases and the latest research papers.

[1540] Specific operation: The server retrieves information from medical journals and other medical sources through APIs and stores it in an internal database.

[1541] Step 2:

[1542] The server inputs the collected data into AI to generate information about pregnancy, childbirth, and child-rearing.

[1543] Specific operation: The AI ​​analyzes the collected data and uses a natural language generation algorithm to create sentences that are easy for users to understand.

[1544] Step 3:

[1545] The server distributes the generated information through a user interface (app or website).

[1546] Specific operation: The generated articles and information pages are uploaded to a web server so that users can access them.

[1547] 2. Providing personalized advice to users

[1548] Step 1:

[1549] Users enter their profile information into the device (e.g., age, number of weeks pregnant, health status).

[1550] Specific operation: The device displays a profile entry form and, once completed, sends the data to the server.

[1551] Step 2:

[1552] The user inputs a specific question into the terminal.

[1553] Specific operation: The terminal displays a question form, and when the user enters a question and presses the send button, the question data is sent to the server.

[1554] Step 3:

[1555] The server inputs the user's profile information and questions into the AI ​​to generate personalized advice.

[1556] What it does: The AI ​​searches the database and creates personalized advice based on relevant information.

[1557] Step 4:

[1558] The server transmits the generated advice to the user terminal.

[1559] Specific operation: The created answer is delivered to the device in real time.

[1560] 3. Health care for mothers and children

[1561] Step 1:

[1562] Users input their daily health data (weight, body temperature, dietary content, etc.) into the device.

[1563] Specific operation: The terminal provides an input interface, and after data is entered, pressing the send button sends the data to the server.

[1564] Step 2:

[1565] The terminal transmits the input data to the server.

[1566] Specific operation: The device sends data to the server via an HTTP request or API.

[1567] Step 3:

[1568] The server analyzes the received data using AI and monitors the health status.

[1569] What it does: The AI ​​analyzes the data, checks for any anomalies, and runs algorithms to assess whether it's within the normal range.

[1570] Step 4:

[1571] The server generates feedback for the user based on the analysis results and sends it to the device.

[1572] Specific operation: Analysis results and recommended actions are sent to the device in real time.

[1573] 4. Mental health support

[1574] Step 1:

[1575] The server periodically sends a stress check questionnaire to the terminal.

[1576] Specific operation: The server generates a stress check form and sends it to the terminal on the specified schedule.

[1577] Step 2:

[1578] The user answers the questionnaire and enters it into the terminal.

[1579] Specific operation: The terminal provides an interface for answering the survey questions and displays a button to submit the answers.

[1580] Step 3:

[1581] The terminal sends the questionnaire responses to the server.

[1582] Specific operation: Survey response data is sent to the server via HTTP request or API.

[1583] Step 4:

[1584] The server analyzes the response data using AI and evaluates stress levels.

[1585] What it does: The AI ​​analyzes your answers and runs an algorithm to quantify your stress level.

[1586] Step 5:

[1587] Based on the analysis results, the server suggests relaxation methods and sends them to the device.

[1588] Specific operation: Generate proposal content and send it to the terminal.

[1589] 5. Community Recommendations

[1590] Step 1:

[1591] The server recommends appropriate communities based on the user's profile.

[1592] Specific Operation: The server parses the profile information and generates a list of appropriate communities.

[1593] Step 2:

[1594] Users join recommended communities.

[1595] Specific operation: The terminal provides a participation interface and displays a participation button.

[1596] Step 3:

[1597] Users share information and experiences within the community.

[1598] Specific operation: The device provides messaging and posting functions to share information with other users.

[1599] 6. Memories storage

[1600] Step 1:

[1601] Users upload ultrasound images and photos of their child's growth record to the device.

[1602] Specific operation: The terminal provides a photo upload interface and sends the uploaded photos to the server.

[1603] Step 2:

[1604] The server analyzes the uploaded photos using facial recognition technology.

[1605] How it works: The AI ​​analyzes the photo data and runs an algorithm to identify important people in the photos.

[1606] Step 3:

[1607] The server selects important photos and generates an automatic album.

[1608] Specific operation: Organize photos chronologically and generate a digital album layout for the user.

[1609] Step 4:

[1610] The server transmits the generated album to the terminal.

[1611] Specific Actions: Create a digital album and provide a link for users to access it.

[1612] Example 1

[1613] 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."

[1614] Conventional information systems related to pregnancy, childbirth, and child-rearing only provide general information, making it difficult for individual users to obtain information and advice that is optimized for them. Furthermore, centralized management of health data and mental health support were insufficient, making it impossible to provide the comprehensive support that users need.

[1615] 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.

[1616] In this invention, the server includes a means for collecting user data, a means for generating information about pregnancy, childbirth, and child-rearing based on the collected data, and a means for distributing the generated information to the user. This enables personalized information and support. The system also includes a means for generating and providing personalized advice based on the user's questions, a means for managing, analyzing, and monitoring health data, a means for conducting and analyzing stress checks to support the user's mental health, and suggesting appropriate relaxation methods, a means for recommending online communities and allowing users to share information, and a means for analyzing uploaded images, selecting appropriate images, and generating a digital album. This allows users to receive comprehensive, personalized support, providing multifaceted support such as health management, mental health care, and promoting information sharing.

[1617] "User data" refers to data including profile information, health information, questions, etc. entered by the user.

[1618] "Information generation" is the process of generating information about pregnancy, childbirth, and parenting based on collected data.

[1619] "Information distribution" is the process of sending the generated information to the user's terminal and making it viewable.

[1620] "Personalized advice" is specific advice that is generated based on a user's individual questions and profile information.

[1621] "Health data management" is the process of collecting, analyzing, and monitoring user and child health information.

[1622] "Mental health support" is the process of conducting stress checks, analyzing stress levels, and suggesting appropriate relaxation methods to support the mental health of users.

[1623] "Online community recommendation" is the process of recommending appropriate communities based on a user's profile and encouraging them to join.

[1624] "Digital album generation" is the process of analyzing uploaded images, selecting important images, and creating a digital album.

[1625] "External data collection" is the process of obtaining data from external medical databases and research materials and storing it in an internal database.

[1626] "Personalized advice" refers to customized advice generated based on a user's profile information, health status, pregnancy stage, and health concerns.

[1627] MODE FOR CARRYING OUT THE INVENTION

[1628] This invention is a comprehensive system for providing information and support related to pregnancy, childbirth, and child-rearing, and utilizes AI technology to provide users with personalized information and advice. The purpose of this invention is to help users obtain the information they need in a timely and appropriate manner at each stage of their pregnancy and child-rearing lives.

[1629] 1. Collection of User Data

[1630] Users enter profile information such as age, number of weeks pregnant, health status, and past medical history into a device, which can be a smartphone, tablet, or PC.

[1631] The device sends the collected information to a server using a secure communication protocol (e.g., HTTPS).

[1632] The server validates the received data and stores it in a database, which can be an SQL database or a NoSQL database.

[1633] 2. Information Generation

[1634] The server periodically collects information from external medical databases (e.g., PubMed) and the latest research materials and stores them in an internal database.

[1635] AI models (e.g., GPT-3) analyze collected medical data and generate up-to-date information, including articles and advice on pregnancy, childbirth, and parenting.

[1636] 3. Information distribution

[1637] The server distributes the generated information to users, and in this process, the most appropriate information is selected based on each user's profile.

[1638] Users can access the information through an application or a web interface.

[1639] 4. Providing personalized advice

[1640] The user enters a specific question into the terminal and sends the question to the server.

[1641] The server uses AI to generate personalized advice based on the user's profile information and questions, and sends the answer to the device.

[1642] Example: When a user asks, "What can I do to prevent morning sickness?", the AI ​​will provide specific advice based on the user's number of weeks pregnant, such as "Diets that include ginger are effective."

[1643] 5. Health data management and monitoring

[1644] Users enter their daily health information (e.g., weight, body temperature, dietary details) into the device.

[1645] The terminal transmits this health information to the server.

[1646] The server uses AI to analyze the data and sends an alert if there is an abnormality.

[1647] Example: When a user enters their daily weight, the AI ​​analyzes changes in weight and, if there is a sudden increase, sends a warning to "consult a doctor."

[1648] 6. Mental health support

[1649] The server periodically sends a stress check questionnaire to the user's terminal.

[1650] The user answers the questionnaire and the results are sent to the server.

[1651] The AI ​​model will analyze the survey results and suggest relaxation and stress reduction methods as needed.

[1652] Example: If a user answers in a way that indicates high stress, the AI ​​will suggest "breathing techniques for relaxation."

[1653] 7. Community Recommendations

[1654] The server recommends appropriate online communities based on the user's profile.

[1655] Users join recommended communities and share information and experiences with other members.

[1656] Example: A new mother is recommended a "first-time parenting community."

[1657] 8. Photo analysis and album generation

[1658] Users upload ultrasound images and photos of their child's growth record to the device.

[1659] The server uses facial recognition technology to analyze the uploaded photos and select important ones.

[1660] The server generates a digital album based on the selected photos.

[1661] Example: When a user uploads one ultrasound photo per month, AI analyzes it, organizes it chronologically, and creates a digital album.

[1662] Through these components and processes, the system provides users with personalized information and support, enabling them to achieve the comprehensive support they need at each stage of pregnancy, childbirth, and child-rearing life.

[1663] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1664] Processing flow

[1665] Step 1: Enter user data

[1666] Users fill out a form in the application with profile information such as age, pregnancy stage, health status, and past medical history.

[1667] Input: Age, gestational age, health status, medical history

[1668] Output: Data entered by the user

[1669] Specific behavior: The user enters information into an input field and presses the "Submit" button.

[1670] Step 2: Send user data

[1671] The terminal transmits the input user information to the server.

[1672] Input: Data entered by the user

[1673] Output: Data sent to the server

[1674] Specific operation: The device sends data to the server using the HTTPS protocol.

[1675] Step 3: Save user data

[1676] The server validates the received user information and stores it in the database.

[1677] Input: Submitted user data

[1678] Output: Data stored in the database

[1679] What happens: The server checks the format and validity of the data and inserts it into the database.

[1680] Step 4: Gather external data

[1681] The server collects external medical databases and the latest research materials via API and stores them in an internal database.

[1682] Input: External databases and research materials

[1683] Output: Medical information stored in an internal database

[1684] Specific operation: The server periodically calls the API to collect new data and store it in the database.

[1685] Step 5: Information Generation

[1686] The AI ​​model generates up-to-date information on pregnancy, childbirth, and parenting based on collected medical data and user profiles.

[1687] Input: Medical information stored in an internal database, user profile

[1688] Output: Information provided to the user

[1689] What it does: AI models process data and generate reports and recommendations.

[1690] Step 6: Information distribution

[1691] The server transmits the generated information to the user's terminal.

[1692] Input: Information generated by the AI ​​model

[1693] Output: Information sent to the terminal

[1694] What it does: The server sends a notification to the user's device, making the information available in an app or web interface.

[1695] Step 7: Enter a specific question

[1696] The user enters a specific question into the terminal, which then transmits the question to the server.

[1697] Input: User's specific question

[1698] Output: The question sent to the server

[1699] Specific behavior: The user enters a question in the text box and presses the "Submit" button.

[1700] Step 8: Personalized advice generation

[1701] The server uses AI to generate personalized advice based on the user's questions and profile information and sends it to the device.

[1702] Input: User questions, profile information

[1703] Output: Personalized advice

[1704] What it does: The AI ​​model processes the data, generates specific advice, and sends it to the device.

[1705] Step 9: Enter and submit your health data

[1706] Users enter their daily health information into a terminal, which then transmits it to a server.

[1707] Input: Health information (weight, body temperature, dietary details, etc.)

[1708] Output: Health data sent to the server

[1709] Specific operation: The user enters health information in the app according to the format and presses the "Submit" button.

[1710] Step 10: Analyzing and monitoring health data

[1711] The server uses AI to analyze health data and sends an alert if there are any abnormalities.

[1712] Input: Collected health data

[1713] Output: Analysis results, warnings if necessary

[1714] What it does: The AI ​​model analyzes the data, detects abnormal patterns, generates alerts, and notifies the user.

[1715] Step 11: Mental Health Check

[1716] The server periodically sends a stress check questionnaire to the user, who then answers it.

[1717] Input: Stress check questionnaire response

[1718] Output: Analysis of survey results

[1719] Specific operation: The server sends a survey, the user answers, and the server receives and analyzes the answers.

[1720] Step 12: Suggested relaxation techniques

[1721] The AI ​​model analyzes the results of the stress check and suggests appropriate relaxation methods.

[1722] Input: Analysis results of stress check questionnaire

[1723] Output: Relaxation suggestions

[1724] Specific operation: The AI ​​model analyzes the data, generates the optimal relaxation method for the user, and notifies the device.

[1725] Step 13: Online Community Recommendations

[1726] The server recommends appropriate online communities based on the user's profile.

[1727] Input: User profile information

[1728] Output: Recommended community information

[1729] Specific operation: The server processes the data, selects the most suitable community for the user, and notifies them.

[1730] Step 14: Upload and analyze photos

[1731] Users upload ultrasound images and photos of their child's growth record to the device.

[1732] Input: Uploaded image

[1733] Output: Image data stored on the server

[1734] Specific behavior: The user selects a photo and presses the "Upload" button.

[1735] Step 15: Generate a digital album

[1736] The server uses facial recognition technology to analyze the images, select important images, and generate a digital album.

[1737] Input: Uploaded image data

[1738] Output: Generated digital album

[1739] Specific operation: The AI ​​model analyzes images and automatically generates an album to provide to the user.

[1740] Through these processing steps, the system provides users with personalized information and services, providing comprehensive support at each stage of pregnancy, childbirth, and child-rearing.

[1741] (Application example 1)

[1742] 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."

[1743] Previous information systems related to pregnancy, childbirth, and child-rearing were not able to assist users when selecting products in stores. This made it difficult for expectant mothers and parents to select the appropriate products they needed, and also increased the time and burden it took to search for products in stores. Furthermore, the lack of personalized product recommendations and optimal in-store routing based on individual users' profile information and health status meant that they were unable to provide an efficient and comfortable shopping experience.

[1744] 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.

[1745] In this invention, the server includes: means for collecting user data; means for generating information about pregnancy, childbirth, and child-rearing based on the collected data; means for distributing the generated information to users; means for generating and providing personalized advice based on user questions; means for managing, analyzing, and monitoring maternal and child health data; means for conducting and analyzing stress checks to support users' mental health and suggesting appropriate relaxation methods; means for recommending communities and allowing users to share information; means for analyzing uploaded photos, selecting appropriate photos, and creating albums; and means for recommending appropriate products and suggesting optimal in-store routing based on user profile information. This enables the provision of information and support tailored to the needs of individual users. It also makes it possible to streamline product searches in stores, providing a more comfortable and stress-free shopping experience.

[1746] "User Data" includes information about the user, such as profile information, health status, medical history, pregnancy weeks, and child ages.

[1747] "Information on pregnancy, childbirth, and child-rearing" refers to information related to health care, nutrition, child-rearing techniques, medical services, etc. for mothers and their children during pregnancy and after birth.

[1748] "Personalized advice" refers to providing customized advice tailored to a user's specific needs and circumstances based on their individual profile information and health status.

[1749] "Health data" refers to health-related information such as the weight, temperature, dietary habits, and medical records of the mother and child.

[1750] A "stress check" is a method of conducting a questionnaire or test to evaluate a user's mental state and analyzing the results.

[1751] "Relaxation methods" refer to specific techniques for reducing stress and achieving mental stability, such as breathing exercises and meditation.

[1752] A "community" refers to an online platform where users with similar circumstances can share information and experiences.

[1753] "Photo analysis" refers to the technology of analyzing image data uploaded by users and classifying or evaluating its content.

[1754] "Album generation" is the process of creating an automatically organized digital or physical photo album based on the analyzed photos.

[1755] "Product recommendation" is a means of selecting and suggesting products suitable for pregnancy and child-rearing based on the user's profile information.

[1756] "Routing" refers to providing optimal routes to help users efficiently find the desired product within a store.

[1757] This invention is a system that provides information and support related to pregnancy, childbirth, and child-rearing. This system collects user data and uses that data to generate information, provide advice, recommend products, and navigate within stores. Specific embodiments for implementing this system are described below.

[1758] 1. Collection of User Data

[1759] Using a device (such as a smartphone), the user enters their profile information, including age, number of weeks pregnant, health status, past medical history, and age of children. The device collects this information and sends it to a server, which stores the received data in a database.

[1760] 2. Information generation

[1761] The server periodically collects data from external medical databases and research papers and stores it in an internal database. Using AI technology, the server generates up-to-date information on pregnancy, childbirth, and parenting, and provides it through an interface for users to access. This AI technology includes, for example, generative AI models that utilize natural language processing (NLP).

[1762] 3. Information distribution

[1763] The generated information is sent from the server to the user's terminal, where the user can access the information through an application or web interface.

[1764] 4. Providing personalized advice

[1765] When a user types a specific question into the device, the question is sent to the server, where the AI ​​generates personalized advice based on the user's profile information and the question, and sends the answer back to the device.

[1766] 5. Health data management and monitoring

[1767] Users enter their own and their children's health information (weight, body temperature, dietary details, etc.) into the device. The device then sends this data to a server, which uses AI to analyze the data and monitor the health status. If any abnormalities, such as sudden weight gain, are detected, the server will send a warning to the user.

[1768] 6. Mental health support

[1769] The server periodically sends a stress check questionnaire to the user's device and collects the results. The AI ​​analyzes the questionnaire responses and suggests relaxation methods and stress reduction measures as needed.

[1770] 7. Community Recommendations

[1771] The server recommends suitable online communities based on the user's profile, and the user can join the recommended communities and share information and experiences with other members.

[1772] 8. Photo analysis and album generation

[1773] Users upload ultrasound images and photos of their child's growth record to their device, and the server uses facial recognition technology to analyze the images, selects important photos, and automatically creates a digital album.

[1774] 9. Product Recommendations and In-Store Navigation

[1775] Based on the user's profile information, the app recommends appropriate products, such as nutritional supplements and toys suited to the developmental stage of a child or expectant mother. It also displays the location of the recommended products in the store and provides the shortest route, allowing users to find the products efficiently.

[1776] Hardware and software used

[1777] Hardware: Smartphone

[1778] Software: Python, React Native as frontend, MySQL as database

[1779] AI Technology: Generative AI Models that Use Natural Language Processing (NLP)

[1780] Specific examples

[1781] Let's say a user is 20 weeks pregnant and shopping in a brick-and-mortar store. The user opens the in-store app on their smartphone.

[1782] 1. Collection of User Data

[1783] The user enters profile information (age, number of weeks pregnant, health status, etc.) and submits it.

[1784] 2. Providing personalized advice

[1785] When a user asks, "What can I do to combat morning sickness?", the AI ​​will provide personalized advice such as, "Diets containing ginger are effective."

[1786] 3. Health data management and monitoring

[1787] When a user enters their weight, if it is determined that their weight is increasing rapidly, the server will send a warning.

[1788] 4. Product Recommendations and In-Store Navigation

[1789] The system suggests recommended products such as folic acid supplements (A3) and vitamin D supplements (A5) and displays the shortest route within the store.

[1790] Prompt Sentence Examples

[1791] "For a user who is 20 weeks pregnant, please recommend the best products to purchase in a physical store and suggest a route, including specific shelf locations."

[1792] This allows users to shop comfortably and efficiently, while also providing support tailored to individual needs.

[1793] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1794] Step 1:

[1795] User Data Collection:

[1796] The user enters their profile information (age, number of weeks pregnant, health condition, past medical history, age of child, etc.) into the terminal. This input data is sent from the terminal to the server, and the server stores the received data in a database. The input here is the user's profile information, and the output is the user data stored on the server.

[1797] Step 2:

[1798] Information generation:

[1799] The server periodically collects data from external medical databases and research papers and stores it in an internal database. It uses AI technology (generative AI models) to generate up-to-date information on pregnancy, childbirth, and parenting. The input is external medical data and research papers, and the output is the generated up-to-date information.

[1800] Step 3:

[1801] Information distribution:

[1802] The server sends the generated information to the user's device, where the user can view the information through an application or web interface. The input is the generated information, and the output is the delivery of the information to the user's device.

[1803] Step 4:

[1804] Personalized advice provided:

[1805] When a user enters a specific question into the device, the question is sent to the server, where the AI ​​generates personalized advice based on the user's profile information and the question, and sends the answer to the device. The input is the user's question and profile information, and the output is personalized advice.

[1806] Step 5:

[1807] Health data management and monitoring:

[1808] Users enter their own and their children's health information (weight, body temperature, dietary details, etc.) into the device. The device sends this data to a server, which uses AI to analyze the data and monitor the health status. If any abnormalities are detected as a result of this analysis, a warning is sent. The input is the user's health data, and the output is the analysis results and a warning in the event of an abnormality.

[1809] Step 6:

[1810] Mental health support:

[1811] The server periodically sends a stress check questionnaire to the user's device and collects the results. The AI ​​analyzes the questionnaire responses and suggests relaxation methods and stress reduction measures as needed. The input is the questionnaire response data, and the output is the analysis results and suggested relaxation methods.

[1812] Step 7:

[1813] Community Recommendations:

[1814] The server recommends appropriate online communities based on the user's profile information. The user can join the recommended communities and share information and experiences with other members. The input is the user's profile information, and the output is the recommended community information.

[1815] Step 8:

[1816] Photo analysis and album generation:

[1817] Users upload ultrasound images and photos recording their child's growth to their device. The server analyzes the images using facial recognition technology and selects important photos. A digital album is automatically generated based on the selected photos. The input is the photo data uploaded by the user, and the output is the analysis results and the generated digital album.

[1818] Step 9:

[1819] Product recommendations and in-store navigation:

[1820] The server recommends appropriate products based on the user's profile information. The location information of the recommended products is compared with the store map to calculate the optimal route. The user can check the recommended products and their locations, as well as the shortest route within the store, through their device. The input is the user's profile information, store map information, and product data, and the output is recommended product information and the store route.

[1821] 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.

[1822] This invention combines an emotion engine with a comprehensive support system for pregnancy, childbirth, and child-rearing to recognize the user's emotions and provide more accurate, personalized support. The system uses AI technology to collect user data and provides personalized information and advice based on that data. In particular, the invention aims to utilize the user's emotion data to more accurately understand the user's mental health and overall well-being and provide appropriate support tailored to the user's needs.

[1823] Overview of program processing

[1824] 1. How we collect user data

[1825] Users enter their profile information into the device, including their age, pregnancy status, health status, and past medical history.

[1826] The terminal sends this information to the server, which stores it in a database.

[1827] 2. Information generation means

[1828] The server periodically collects data from external medical databases and the latest research papers and stores it in an internal database.

[1829] The AI ​​uses the collected data to generate up-to-date information on pregnancy, childbirth, and parenting, which is then presented through an interface for users to access.

[1830] 3. Information distribution methods

[1831] The server distributes the generated information through a user interface (app or website).

[1832] Users can access this information through an app or web interface.

[1833] 4. Means of personalized advice delivery

[1834] A user enters a specific question into the terminal, which then transmits the question to the server.

[1835] The server uses AI to generate personalized advice based on the user's profile information and questions, and sends the answer to the device.

[1836] Examples:

[1837] When a user asks, "What can I do to combat morning sickness?", the AI ​​will refer to other data that matches the user's profile (for example, the number of weeks pregnant) and provide specific measures, such as "Diets containing ginger are effective."

[1838] 5. Health data management and monitoring measures

[1839] Users enter their own and their children's health information (weight, body temperature, dietary details, etc.) into the device.

[1840] The device sends this data to a server, which then uses AI to analyze the data and monitor the user's health.

[1841] Examples:

[1842] Users enter their daily weight, and the server analyzes the data and sends alerts if their weight is increasing too rapidly.

[1843] 6. Mental health support measures

[1844] The server periodically sends a stress check questionnaire to the user's device and collects the results.

[1845] The AI ​​will analyze the survey responses and suggest relaxation and stress reduction methods as needed.

[1846] Examples:

[1847] If the user answers the questionnaire indicating high stress, the server will suggest "relaxation breathing techniques."

[1848] 7. Community Recommendations

[1849] The server recommends appropriate online communities based on the user's profile.

[1850] Users can join recommended communities and share information and experiences with other members.

[1851] Examples:

[1852] New moms are encouraged to join the "First Time Parenting Community" where they can share information and experiences with other new moms.

[1853] 8. Photo analysis and album generation method

[1854] Users upload ultrasound images and photos of their child's growth record to the device.

[1855] The server uses facial recognition technology to analyze the photos and select the most important ones.

[1856] A digital album is automatically generated based on the selected photos.

[1857] Examples:

[1858] When users upload one ultrasound photo per month, the server organizes them in chronological order and creates a growth record album.

[1859] Combining Emotion Engines

[1860] 9. Emotion Recognition with Emotion Engine

[1861] Users can input their daily moods and emotions through the device, and emotions can also be recognized through voice input and facial expression capture.

[1862] The device sends this emotional data to the server, which then analyzes it using an emotion engine.

[1863] Examples:

[1864] When a user uses the diary function and enters "I'm very tired today," the emotion engine understands "tired" and the server stores that data.

[1865] 10. Personalized advice based on emotional data

[1866] The server adjusts the content and tone of the advice based on the user's emotional data recognized by the emotion engine. For example, if the user is feeling stressed, the server will provide encouraging advice in a gentle tone.

[1867] Users can receive more personalized advice through their devices.

[1868] Examples:

[1869] If the user types "I'm frustrated," the server will offer gentle advice like "Try to relax a bit today."

[1870] 11. Strengthening mental health support

[1871] The emotion engine combines the results of traditional stress tests with emotional data to provide a more accurate mental health assessment.

[1872] Based on this, the server provides more appropriate relaxation methods and necessary support.

[1873] Examples:

[1874] If the user shows high stress in the stress check and the emotional data indicates "anxiety," the server will not only provide "deep breathing and meditation" methods but also recommend "booking a counseling appointment."

[1875] Through the above components and processes, this system comprehensively provides the information and support needed at each stage of pregnancy, childbirth, and child-rearing. This allows each user to not only obtain the information that is most suited to them, but also receive psychological support tailored to their emotions. Furthermore, by sharing information with other users in the same situation through the community function, users can receive even more comprehensive support.

[1876] The processing flow will be explained below.

[1877] 1. Generating information about pregnancy, childbirth, and child-rearing

[1878] Step 1:

[1879] The server periodically collects data from external medical databases and the latest research papers.

[1880] Specific operation: The server retrieves information from medical journals and databases via API and stores it in an internal database.

[1881] Step 2:

[1882] The server inputs the collected data into AI to generate information about pregnancy, childbirth, and child-rearing.

[1883] Specific operation: The AI ​​analyzes the collected data and uses a natural language generation algorithm to create sentences that are easy for users to understand.

[1884] Step 3:

[1885] The server distributes the generated information through a user interface (app or website).

[1886] Specific operation: The generated articles and information pages are uploaded to a web server so that users can access them.

[1887] 2. Providing personalized advice to users

[1888] Step 1:

[1889] Users enter their profile information into the device (e.g., age, number of weeks pregnant, health status).

[1890] Specific operation: The device displays a profile entry form, and once the profile entry is complete, it sends the data to the server.

[1891] Step 2:

[1892] The user inputs a specific question into the terminal.

[1893] Specific operation: The terminal displays a question form, and when the user enters a question and presses the send button, the question data is sent to the server.

[1894] Step 3:

[1895] The server inputs the user's profile information and questions into the AI ​​to generate personalized advice.

[1896] What it does: The AI ​​searches the database and creates personalized advice based on relevant information.

[1897] Step 4:

[1898] The server transmits the generated advice to the user terminal.

[1899] Specific operation: The created answer is delivered to the device in real time.

[1900] 3. Health care for mothers and children

[1901] Step 1:

[1902] Users input their daily health data (weight, body temperature, dietary content, etc.) into the device.

[1903] Specific operation: The terminal provides an input interface, and after data is entered, the data is sent to the server by pressing the send button.

[1904] Step 2:

[1905] The terminal transmits the input data to the server.

[1906] Specific operation: The device sends data to the server via an HTTP request or API.

[1907] Step 3:

[1908] The server analyzes the received data using AI and monitors the health status.

[1909] What it does: The AI ​​analyzes the data, checks for any anomalies, and runs algorithms to assess whether it's within the normal range.

[1910] Step 4:

[1911] The server generates feedback for the user based on the analysis results and sends it to the device.

[1912] Specific operation: Analysis results and recommended actions are sent to the device in real time.

[1913] 4. Mental health support

[1914] Step 1:

[1915] The server periodically sends a stress check questionnaire to the terminal.

[1916] Specific operation: The server generates a stress check form and sends it to the terminal based on the specified schedule.

[1917] Step 2:

[1918] The user answers the questionnaire and enters it into the terminal.

[1919] Specific operation: The terminal provides an interface for answering the survey questions, and after entering the answer, displays a submit button.

[1920] Step 3:

[1921] The terminal sends the questionnaire responses to the server.

[1922] Specific operation: The device sends the response data to the server via an HTTP request or API.

[1923] Step 4:

[1924] The server analyzes the response data using AI and evaluates stress levels.

[1925] What it does: The AI ​​analyzes your answers and runs an algorithm to quantify your stress level.

[1926] Step 5:

[1927] Based on the analysis results, the server suggests relaxation methods and sends them to the device.

[1928] Specific operation: Generate proposal content and send it to the terminal.

[1929] 5. Community Recommendations

[1930] Step 1:

[1931] The server recommends appropriate communities based on the user's profile.

[1932] Specific Operation: The server parses the profile information and generates a list of appropriate communities.

[1933] Step 2:

[1934] Users join recommended communities.

[1935] Specific operation: The terminal provides a participation interface and displays a participation button.

[1936] Step 3:

[1937] Users share information and experiences within the community.

[1938] Specific operation: The device provides messaging and posting functions to share information with other users.

[1939] 6. Memories storage

[1940] Step 1:

[1941] Users upload ultrasound images and photos of their child's growth record to the device.

[1942] Specific operation: The terminal provides a photo upload interface and sends the uploaded photo data to the server.

[1943] Step 2:

[1944] The server analyzes the uploaded photos using facial recognition technology.

[1945] How it works: The AI ​​analyzes the photo data and runs an algorithm to identify important people in the photos.

[1946] Step 3:

[1947] The server selects important photos and generates an automatic album.

[1948] Specific operation: Organize photos chronologically and generate a digital album layout for the user.

[1949] Step 4:

[1950] The server transmits the generated album to the terminal.

[1951] Specific Actions: Create a digital album and provide a link for users to access it.

[1952] 7. Emotion Recognition with Emotion Engine

[1953] Step 1:

[1954] Users can input their moods and emotions into the device, and voice input and facial recognition are also available for facial expression capture.

[1955] Specific operation: The device provides an emotion input interface and collects voice and facial expression data.

[1956] Step 2:

[1957] The terminal transmits the emotion data to the server.

[1958] Specific operation: Sends voice and facial expression data to the server via HTTP request or API.

[1959] Step 3:

[1960] The server uses an emotion engine to analyze the transmitted emotion data.

[1961] Specific operation: Analyzes data using emotion recognition algorithms to determine the user's emotional state.

[1962] 8. Personalized advice based on emotional data

[1963] Step 1:

[1964] The server adjusts the content and tone of the advice based on the emotional data recognized by the emotion engine.

[1965] Specific operation: The newly acquired emotion data is applied to the advice generation algorithm to generate appropriate advice.

[1966] Step 2:

[1967] The server transmits the generated advice to the user terminal.

[1968] Specific operation: Advice content is delivered to the device in real time.

[1969] 9. Strengthening mental health support

[1970] Step 1:

[1971] The emotion engine integrates stress check results with emotional data to provide a more accurate mental health assessment.

[1972] How it works: An analytical algorithm combines stress levels and emotional data to assess your overall mental health.

[1973] Step 2:

[1974] Based on the overall evaluation results, the server will suggest further appropriate relaxation methods and support.

[1975] Specific operation: Generate proposal content and send it to the terminal.

[1976] Through the above processing steps, information and support related to pregnancy, childbirth, and child-rearing are provided to users. By utilizing the emotion engine, the system effectively supports the user's mental health and provides personalized information and advice according to their physical condition and emotions.

[1977] Example 2

[1978] 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."

[1979] Conventional information systems related to pregnancy, childbirth, and child-rearing have struggled to provide information and advice tailored to each user's individual circumstances and emotions. Furthermore, methods for comprehensively supporting users' mental health have been limited. Furthermore, there is a need for a comprehensive system that can provide a wide range of support, including photo management and community recommendation functions.

[1980] 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.

[1981] In this invention, the server includes means for collecting user data, means for generating information about pregnancy, childbirth, and child-rearing based on the collected data, means for distributing the generated information to users, means for generating and providing personalized advice based on user questions, means for collecting, analyzing, and monitoring individual health information, means for analyzing emotional data and suggesting relaxation methods as needed to support the user's mental health, means for recommending communities and sharing information among users, means for analyzing uploaded image data, selecting appropriate photos, and generating albums, means for collecting and analyzing user emotional data using an emotion engine, and means for providing personalized advice based on the analyzed emotional data. This allows users to receive information and support optimized for their own situation and emotions.

[1982] "User data" refers to information about system users, including profile information, health status, number of weeks pregnant, and past medical history.

[1983] "Means for collecting" refers to a method or device for having a user input data, transmitting it from the terminal to a server, and storing it in a database.

[1984] "Means for generating information" refers to methods and devices that use AI or servers to create useful information about pregnancy, childbirth, and child-rearing based on collected data.

[1985] The "means for distributing" refers to a method or device for distributing the generated information to a user's terminal.

[1986] "Personalized advice" refers to advice or suggestions that are tailored to a user's specific situation based on their individual information.

[1987] "Means for collecting, analyzing, and monitoring health information" refers to methods and devices that collect and analyze data related to the health of users and their children, and monitor the results regularly.

[1988] "Means for suggesting relaxation methods to support mental health" refers to a method or device that analyzes the user's emotions and stress state and suggests appropriate relaxation methods or stress reduction measures based on the results.

[1989] "Means for recommending communities and sharing information" refers to a method or device for recommending appropriate online communities based on user profile data and supporting information exchange among users within those communities.

[1990] "Means for analyzing image data and generating an album" refers to a method or device that analyzes photos and image data uploaded by users, selects important images, and automatically generates a digital album.

[1991] An "emotion engine" refers to software or algorithms that recognize and analyze emotions from user input data, voice, facial expression data, etc.

[1992] This invention combines an emotion engine with a comprehensive support system for pregnancy, childbirth, and child-rearing to recognize the user's emotions and provide more accurate, personalized support. The system uses AI technology to collect user data and provides personalized information and advice based on that data. In particular, the invention aims to utilize the user's emotion data to more accurately understand the user's mental health and overall well-being and provide appropriate support tailored to the user's needs.

[1993] How user data is collected

[1994] The user enters their profile information into the device, such as their age, number of weeks pregnant, health status, and past medical history.

[1995] The terminal sends this information to a server, which stores it in a database. The software used here is a database management system (DBMS).

[1996] Information generation means

[1997] The server periodically collects data from external medical databases and the latest research papers and stores it in an internal database.

[1998] The AI ​​uses the collected data to generate up-to-date information about pregnancy, childbirth, and parenting, which is then presented through a user interface. The software used is an AI model equipped with natural language processing (NLP) algorithms.

[1999] Information distribution method

[2000] The server distributes the generated information through a user interface (app or website).

[2001] Users can access this information through an app or web interface. The software used here is a web application framework and a mobile application platform.

[2002] Personalized advice delivery methods

[2003] A user enters a specific question into the terminal, which then transmits the question to the server.

[2004] The server uses AI to generate personalized advice based on the user's profile information and questions, and sends the answer to the device.

[2005] Examples:

[2006] When a user asks, "What can I do to combat morning sickness?", the AI ​​will refer to other data that matches the user's profile (e.g., number of weeks pregnant) and provide specific measures such as "Diets containing ginger are effective." An example of a prompt sentence in this case is, "What can I do to combat morning sickness?"

[2007] Health data management and monitoring tools

[2008] Users enter their own and their children's health information (weight, body temperature, dietary details, etc.) into the device.

[2009] The device sends this data to a server, which then uses AI to analyze the data and monitor the user's health.

[2010] Examples:

[2011] When a user enters their daily weight, the server analyzes the data and sends a warning if their weight is increasing rapidly. An example of a prompt sentence is "Your weight today is 80 kg."

[2012] Mental health support measures

[2013] The server periodically sends a stress check questionnaire to the user's device and collects the results.

[2014] The AI ​​will analyze the survey responses and suggest relaxation and stress reduction methods as needed.

[2015] Examples:

[2016] If the user answers the questionnaire indicating high stress, the server will suggest "breathing exercises for relaxation." An example of a prompt is "How often have you felt stressed recently?"

[2017] Community Recommendations

[2018] The server recommends appropriate online communities based on the user's profile.

[2019] Users can join recommended communities and share information and experiences with other members.

[2020] Examples:

[2021] New moms are encouraged to join a "first-time parenting community" where they can share information and experiences with other new moms. An example of a prompt is "Do you want to make mommy friends?"

[2022] Photo analysis and album generation tool

[2023] Users upload ultrasound images and photos of their child's growth record to the device.

[2024] The server uses facial recognition technology to analyze the photos and select the most important ones.

[2025] A digital album is automatically generated based on the selected photos.

[2026] Examples:

[2027] When a user uploads one ultrasound photo per month, the server organizes them in chronological order and creates a growth record album. An example of a prompt is "Please upload this month's ultrasound photo."

[2028] Combining Emotion Engines

[2029] Emotion recognition by emotion engine

[2030] Users can input their daily moods and emotions through the device, and emotions can also be recognized through voice input and facial expression capture.

[2031] The device sends this emotional data to the server, which then analyzes it using an emotion engine.

[2032] Examples:

[2033] When a user uses the diary function and enters "I'm very tired today," the emotion engine understands "tired" and the server stores the data. An example of a prompt sentence is "Please tell me how you feel today."

[2034] Personalized advice based on emotional data

[2035] The server adjusts the content and tone of the advice based on the user's emotional data recognized by the emotion engine. For example, if the user is feeling stressed, the server will provide encouraging advice in a gentle tone.

[2036] Users can receive more personalized advice through their devices.

[2037] Examples:

[2038] If the user types "I'm frustrated," the server might offer gentle advice such as "Try to relax a bit today." An example of a prompt sentence is "I'm frustrated, what should I do?"

[2039] Strengthening mental health support

[2040] The emotion engine combines the results of traditional stress tests with emotional data to provide a more accurate mental health assessment.

[2041] Based on this, the server provides more appropriate relaxation methods and necessary support.

[2042] Examples:

[2043] If the user's stress check indicates high stress and the emotional data indicates "anxiety," the server will not only provide "deep breathing and meditation" methods but also recommend "booking a counseling appointment." An example of a prompt sentence is, "I've been feeling a lot of anxiety lately. What should I do?"

[2044] Through the above components and processes, this system comprehensively provides the information and support needed at each stage of pregnancy, childbirth, and child-rearing. This allows each user to not only obtain the information that is most suited to them, but also receive psychological support tailored to their emotions. Furthermore, by sharing information with other users in the same situation through the community function, users can receive even more comprehensive support.

[2045] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2046] Step 1: Enter and submit user data

[2047] The user enters their profile information into the device, such as age, pregnancy status, health status, and past medical history.

[2048] Input: User profile information

[2049] The terminal sends the entered information to the server. Specifically, when data is entered through a form and the send button is pressed, the data is sent to the server in real time.

[2050] Output: User data sent to the server

[2051] Specific operation: The user enters information into the profile entry screen of the app and presses the send button. The device then sends the data to the server.

[2052] Step 2: Save user data

[2053] The server receives the user data sent from the terminal and stores it in a database using a database management system (DBMS).

[2054] Input: User data sent from the terminal

[2055] Output: User data stored in the database

[2056] Specific operation: The server uses the database API to retrieve the received data and save it in the database.

[2057] Step 3: Collect medical data

[2058] The server collects data from external medical databases and the latest research papers and stores it in an internal database.

[2059] Input: External medical databases and research papers

[2060] Output: Medical data stored in an internal database

[2061] Specific operation: The server periodically collects medical data using an external API and stores it in its own database.

[2062] Step 4: Information Generation

[2063] The AI ​​built into the server generates the latest information on pregnancy, childbirth, and child-rearing based on user and medical data.

[2064] Input: User data, medical data

[2065] Output: Latest information generated

[2066] How it works: The AI ​​model analyzes the user's profile information and the latest medical data to generate information appropriate for the user.

[2067] Step 5: Distributing information

[2068] The server delivers the generated information to the user through a user interface (app or website).

[2069] Input: Latest generated information

[2070] Output: Information delivered to the user

[2071] Specific behavior: The server generates information and sends it to a user interface using an API to display it on the app's home screen or website dashboard.

[2072] Step 6: Enter and submit your specific question

[2073] The user types a specific question into the device, such as "Please tell me what to do about morning sickness."

[2074] Input: User's specific question

[2075] The terminal sends a query to the server.

[2076] Output: The query data sent to the server

[2077] Specific operation: The user enters a specific question into the question input field of the app and presses the send button. The device then sends the question data to the server.

[2078] Step 7: Generate personalized advice

[2079] The server uses AI to generate personalized advice based on the user's profile information and questions.

[2080] Input: User profile information, specific questions

[2081] Output: Generated personalized advice

[2082] How it works: The AI ​​model references the user's profile and question to generate the most appropriate advice.

[2083] Step 8: Distributing Advice

[2084] The server transmits the generated advice to the terminal.

[2085] Input: Generated personalized advice

[2086] Output: Advice delivered to the terminal

[2087] Specific operation: The server uses an API to send the generated advice data to the terminal and notifies the user's terminal.

[2088] Step 9: Enter and submit your health information

[2089] Users enter their own and their children's health information into the device, such as weight, body temperature, and dietary details.

[2090] Input: Health information

[2091] The terminal transmits this data to the server.

[2092] Output: Health data sent to the server

[2093] Specific operation: The user enters health information into the app and presses the send button. The device then sends the data to the server.

[2094] Step 10: Health data storage and analysis

[2095] The server stores the submitted health data in a database and analyzes it using AI.

[2096] Input: Health data

[2097] Output: Analyzed health data

[2098] How it works: The server receives health data and stores it in a database. The AI ​​model analyzes the data and monitors for abnormalities.

[2099] Step 11: Submit the stress check questionnaire

[2100] The server periodically sends a stress check questionnaire to the user's terminal.

[2101] Input: Stress check questionnaire

[2102] Output: Survey sent to user's device

[2103] Specific operation: The server uses an API to send stress check questionnaire data to the terminal and submits questionnaires to the user at high frequency.

[2104] Step 12: Complete and submit the survey

[2105] The user answers the stress check questionnaire.

[2106] Input: Stress check questionnaire response

[2107] The terminal sends the response to the server.

[2108] Output: Survey responses sent to the server

[2109] Specific operation: The user answers the questionnaire and presses the send button. The device sends the answer data to the server.

[2110] Step 13: Analyze stress data and propose relaxation methods

[2111] The server uses AI to analyze the questionnaire responses and suggest relaxation methods as needed.

[2112] Input: Survey response data

[2113] Output: Proposed relaxation method

[2114] Specific operation: The AI ​​model analyzes stress data, devises stress reduction measures, and suggests them to the user.

[2115] Step 14: Community Recommendations

[2116] The server recommends appropriate online communities based on the user's profile.

[2117] Input: User profile information

[2118] Output: Community recommendations

[2119] Specific operation: The server analyzes the profile information and generates a list of recommended communities.

[2120] Step 15: Upload and analyze photos

[2121] Users upload ultrasound images and photos of their child's growth record to the device.

[2122] Input: Ultrasound photos and growth record photos

[2123] The device sends the photo to the server.

[2124] Output: Photo data sent to the server

[2125] Specific operation: The user uploads a photo in the specified location in the app, and the device sends it to the server.

[2126] Step 16: Create an album

[2127] The server uses facial recognition technology to analyze the photos, select important photos, and generate a digital album.

[2128] Input: Photo data

[2129] Output: Digital album

[2130] Specific operation: The server analyzes the photo data, organizes it chronologically, and generates a growth record album.

[2131] Step 17: Enter and send emotion data

[2132] The user inputs emotions into the device, including voice input and facial expression capture.

[2133] Input: Emotion data

[2134] The terminal transmits the emotion data to the server.

[2135] Output: Emotion data sent to the server

[2136] Specific operation: The user inputs data expressing emotions into the terminal, and the terminal transmits the data to the server.

[2137] Step 18: Analyze and store emotion data

[2138] The server uses an emotion engine to analyze the emotion data and saves the results.

[2139] Input: Emotion data

[2140] Output: Parsed emotion data

[2141] Specific operation: The emotion engine analyzes the emotion data and stores it in the server's database.

[2142] Step 19: Generating personalized advice based on sentiment data

[2143] The server adjusts the content and tone of the advice based on the emotional data recognized by the emotion engine.

[2144] Input: Parsed emotion data

[2145] Output: Adjusted advice

[2146] Specific operation: The AI ​​generates advice that reflects emotional data and provides it in a form appropriate for the user.

[2147] Step 20: Providing personalized advice

[2148] The server delivers the tailored advice to the user's terminal.

[2149] Input: Tailored Advice

[2150] Output: Advice delivered to the user's device

[2151] Specific operation: The server sends the generated advice data to the device so that the user can view it in the app.

[2152] In this way, the system provides comprehensive and personalized support to users while performing a wide range of data collection, analysis, information generation and distribution.

[2153] (Application example 2)

[2154] 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."

[2155] Support systems for pregnancy, childbirth, and child-rearing are required to accurately grasp the emotional state and health information of individual users and provide appropriate advice and support in real time. However, conventional systems have difficulty responding to emotional changes in a personalized manner, and have not been able to provide sufficient satisfaction to users. Furthermore, to improve the quality of advice in physical stores, flexible responses according to the customer's emotional state are necessary.

[2156] 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 user data, means for generating information about pregnancy, childbirth, and child-rearing based on the collected data, means for distributing the generated information to the user, means for generating and providing personalized advice based on the user's questions, means for managing, analyzing, and monitoring health data of the mother and child, means for conducting and analyzing stress checks to support the user's mental health and suggesting appropriate relaxation methods, means for recommending communities and allowing users to share information, means for analyzing uploaded photos, selecting appropriate photos, and generating albums, means for analyzing the user's emotional state based on emotional data and adjusting the content and tone of personalized advice, and means for recognizing customer emotions in real time at a physical store and providing individual counseling and advice tailored to the situation. This allows users to receive personalized advice and support in real time based on their emotions and health condition.

[2157] "User Data" is a set of data about a user, such as the user's profile information, health information, and emotional state.

[2158] A "means for collecting" is a method or device for inputting, obtaining, or detecting user data.

[2159] The "means for generating information" refers to a method or device for generating information related to pregnancy, childbirth, and child-rearing based on collected user data.

[2160] "Means for distributing information" refers to a method or device for providing the generated information to users.

[2161] "Personalized advice" is advice that is specifically tailored to a user's question or situation.

[2162] "Health data" refers to data such as the weight, temperature, and health status of the mother and child.

[2163] "Management, analysis and monitoring means" refers to a set of methods or devices for collecting health data, analyzing and monitoring it, and providing appropriate support to users.

[2164] A "stress check" is a questionnaire or assessment conducted to assess a user's mental health.

[2165] "Relaxation techniques" refer to breathing techniques, meditation, relaxation techniques, etc. that are used to reduce mental stress.

[2166] A "community" is a group or online forum where users with a common interest share information and experiences.

[2167] The "means for analyzing photos and generating an album" refers to a method or device for analyzing uploaded photos, selecting important images, and creating a digital album.

[2168] "Emotion data" is data that indicates the user's daily mood and emotional state.

[2169] The "means for analyzing emotional state" refers to a method or device for recognizing and evaluating the user's emotions based on emotional data.

[2170] A "brick and mortar store" is a physical store where customers receive goods or services in person.

[2171] A "means for recognizing customer emotions in real time" is a method or device that can instantly grasp a customer's current emotions.

[2172] "Means for providing counseling and advice" refers to a method or device that provides appropriate support in response to the user's feelings and questions.

[2173] This invention is a comprehensive support system for pregnancy, childbirth, and child-rearing, which recognizes the user's emotions by combining an emotion engine and provides more accurate and personalized support. An embodiment of this system will be described in detail below.

[2174] Hardware and software used

[2175] Hardware: smartphones, tablets, back-end servers

[2176] Software: Emotion recognition engine, AI model (e.g., TensorFlow, GPT-3), database (e.g., MySQL, Firebase), user interface (e.g., Vue.js, React Native)

[2177] System Program

[2178] First, user data is collected, where users enter their profile information, health information, and daily emotional state using a smartphone or tablet device, and this data is sent in real time to a back-end server and stored in a database.

[2179] Next, AI generates information about pregnancy, childbirth, and child-rearing based on the collected data. It compares and analyzes user data stored in the database with data collected from external medical databases and the latest research papers. This generates the most up-to-date and accurate information and provides it to users.

[2180] The generated information is delivered to the user through an interface. When a user enters a question through an app or tablet, the question is sent to the server. The server uses AI to generate personalized advice based on the question and the user's profile information and sends it back to the device.

[2181] The user data also includes health data of the mother and child, which is managed, analyzed, and monitored by the server. If any abnormalities are found in the health data, warnings and countermeasures are automatically proposed.

[2182] Supporting mental health is also an important element. The server periodically sends users stress check questionnaires and analyzes their responses. The emotion engine recognizes the user's emotional state and then personalized suggestions are made for relaxation and stress reduction.

[2183] The system also has a photo analysis and album generation function. Ultrasound photos and growth record photos uploaded by users are analyzed using AI, and important photos are automatically selected and created as a digital album.

[2184] Finally, we will explain how this system can be applied to physical stores. When customers visit a physical store, they can input their emotional state on the spot using a smartphone or tablet, or their emotional state can be analyzed in real time by an emotion recognition engine. This information is immediately sent to a server, which then provides appropriate counseling or advice.

[2185] Examples of concrete examples and prompts

[2186] For example, if a customer visiting a physical store types in "I feel irritated while breastfeeding," the emotion engine will recognize the word "irritation," and the AI ​​model will suggest "simple breathing exercises to help you relax" based on profile data such as the number of weeks pregnant and health status. It will also recommend places to purchase relaxation products and nearby mental health support organizations.

[2187] Prompt Sentence Examples

[2188] Ask the AI ​​model the following prompt:

[2189] User profile data: Age: "30", Pregnancy week: "20 weeks", Health status: "Normal"

[2190] Emotional data: "I'm feeling very frustrated today."

[2191] Q: "What can I do to reduce frustration while breastfeeding?"

[2192] Answer: "Try some breathing exercises to help you relax, especially taking deep breaths. Also, consider using relaxation aids."

[2193] In this way, the embodiments of the invention can provide personalized advice and support in real time according to the user's emotions and health condition.

[2194] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2195] Step 1:

[2196] A user uses a smartphone or tablet device to input their profile information, health information, and daily emotional state. This includes age, pregnancy week, health condition, and emotion (e.g., "I'm irritated"). The input data is sent from the device to a server in real time. The server receives this data and stores it in a database. Here, the input is the user's profile information and emotional data, and the output is the user data stored in the database.

[2197] Step 2:

[2198] The server generates information about pregnancy, childbirth, and child-rearing based on user data stored in the database and data collected from external medical databases and the latest research papers. An AI model (e.g., TensorFlow or GPT-3) processes this information and generates up-to-date and accurate information. The input is user data and external data, and the output is the generated up-to-date information.

[2199] Step 3:

[2200] The server delivers the generated information to the user, who then displays it on their smartphone or tablet through a user interface (e.g., Vue.js, React Native). The input is the generated up-to-date information, and the output is the information displayed in the user interface.

[2201] Step 4:

[2202] The user inputs a specific question via an app or tablet. For example, "What can I do if I get irritated while breastfeeding?" The input question is sent from the device to the server. The server uses an AI model to generate personalized advice based on the question and the user's profile information, and sends it back to the device. The input is the user's question and profile information, and the output is personalized advice.

[2203] Step 5:

[2204] The health data of the user's mother and child is managed, analyzed, and monitored by a server. The user enters health data (e.g., weight, temperature) into the device and sends it to the server. The server analyzes this data using AI, and if any abnormalities are detected, it automatically issues warnings and suggests countermeasures. The input is health data, and the output is the analysis results and countermeasures.

[2205] Step 6:

[2206] The server periodically sends a stress check questionnaire to the user's device. The user answers the questionnaire and the data is sent to the server. The server uses an emotion recognition engine to analyze the user's emotional state and suggests relaxation methods and stress reduction measures. The input is the questionnaire response data and emotional data, and the output is the suggested relaxation methods.

[2207] Step 7:

[2208] The server recommends suitable online communities to users through the community function. It selects and recommends relevant communities based on the user's profile information. The input is the user's profile information, and the output is the recommended communities.

[2209] Step 8:

[2210] Users upload ultrasound images and growth record photos to their device. The server uses AI to analyze them, selects important photos, and generates a digital album. The input is the uploaded photos, and the output is the generated digital album.

[2211] Step 9:

[2212] In physical stores, customers input their emotional state using a smartphone or tablet, and the device's emotion recognition engine analyzes their emotional state in real time. The information is immediately sent to the server, which then provides appropriate counseling and advice. The input is the emotional data of the physical store customer, and the output is real-time counseling and advice.

[2213] 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.

[2214] 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.

[2215] 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.

[2216] [Fourth embodiment]

[2217] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[2218] 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.

[2219] 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).

[2220] 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.

[2221] 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.

[2222] 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).

[2223] 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.

[2224] 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.

[2225] 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.

[2226] 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.

[2227] 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.

[2228] 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.

[2229] 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."

[2230] This invention is a system that provides a series of information and support related to pregnancy, childbirth, and child-rearing, and its core is information generation and personalization using AI technology. The components of this system consist of various means for collecting user data and providing information and advice generated based on that data.

[2231] Overview of program processing

[2232] 1. How we collect user data

[2233] Users first enter their profile information into the device, including their age, number of weeks pregnant, health status, and past medical history.

[2234] The terminal sends this information to the server, which stores it in a database.

[2235] 2. Information generation means

[2236] The server periodically collects data from external medical databases and the latest research papers and stores it in an internal database.

[2237] The AI ​​uses the collected data to generate up-to-date information on pregnancy, childbirth, and parenting, which is then presented through an interface for users to access.

[2238] 3. Information distribution methods

[2239] The server sends the generated information to the device for viewing by the user, who can access this information through an app or web interface.

[2240] 4. Means of personalized advice delivery

[2241] A user enters a specific question into the terminal, which then transmits the question to the server.

[2242] The server uses AI to generate personalized advice based on the user's profile information and questions, and sends the answer to the device.

[2243] Examples:

[2244] When a user asks, "What can I do to combat morning sickness?", the AI ​​will refer to other data that matches the user's profile (for example, the number of weeks pregnant) and provide specific measures, such as "Diets containing ginger are effective."

[2245] 5. Health data management and monitoring measures

[2246] Users enter their own and their children's health information (weight, body temperature, dietary details, etc.) into the device.

[2247] The device sends this data to a server, which then uses AI to analyze the data and monitor the user's health.

[2248] Examples:

[2249] Users enter their daily weight, and the server analyzes the data and sends alerts if their weight is increasing too rapidly.

[2250] 6. Mental health support measures

[2251] The server periodically sends a stress check questionnaire to the user's device and collects the results.

[2252] The AI ​​will analyze the survey responses and suggest relaxation and stress reduction methods as needed.

[2253] Examples:

[2254] If the user answers the questionnaire indicating high stress, the server will suggest "relaxation breathing techniques."

[2255] 7. Community Recommendations

[2256] The server recommends appropriate online communities based on the user's profile.

[2257] Users can join recommended communities and share information and experiences with other members.

[2258] Examples:

[2259] New moms are encouraged to join the "First Time Parenting Community" where they can share information and experiences with other new moms.

[2260] 8. Photo analysis and album generation method

[2261] Users upload ultrasound images and photos of their child's growth record to the device.

[2262] The server uses facial recognition technology to analyze the photos and select the most important ones.

[2263] A digital album is automatically generated based on the selected photos.

[2264] Examples:

[2265] When users upload one ultrasound photo per month, the server organizes them in chronological order and creates a growth record album.

[2266] Through the above components and processes, this system comprehensively provides the information and support needed at each stage of pregnancy, childbirth, and child-rearing. This allows each user to not only obtain the information that is most suitable for them, but also receive psychological support. Furthermore, by sharing information with other users in the same situation through the community function, users can receive even more comprehensive support.

[2267] The processing flow will be explained below.

[2268] 1. Generating information about pregnancy, childbirth, and child-rearing

[2269] Step 1:

[2270] The server periodically collects data from external medical databases and the latest research papers.

[2271] Specific operation: The server retrieves information from medical journals and other medical sources through APIs and stores it in an internal database.

[2272] Step 2:

[2273] The server inputs the collected data into AI to generate information about pregnancy, childbirth, and child-rearing.

[2274] Specific operation: The AI ​​analyzes the collected data and uses a natural language generation algorithm to create sentences that are easy for users to understand.

[2275] Step 3:

[2276] The server distributes the generated information through a user interface (app or website).

[2277] Specific operation: The generated articles and information pages are uploaded to a web server so that users can access them.

[2278] 2. Providing personalized advice to users

[2279] Step 1:

[2280] Users enter their profile information into the device (e.g., age, number of weeks pregnant, health status).

[2281] Specific operation: The device displays a profile entry form and, once completed, sends the data to the server.

[2282] Step 2:

[2283] The user inputs a specific question into the terminal.

[2284] Specific operation: The terminal displays a question form, and when the user enters a question and presses the send button, the question data is sent to the server.

[2285] Step 3:

[2286] The server inputs the user's profile information and questions into the AI ​​to generate personalized advice.

[2287] What it does: The AI ​​searches the database and creates personalized advice based on relevant information.

[2288] Step 4:

[2289] The server transmits the generated advice to the user terminal.

[2290] Specific operation: The created answer is delivered to the device in real time.

[2291] 3. Health care for mothers and children

[2292] Step 1:

[2293] Users input their daily health data (weight, body temperature, dietary content, etc.) into the device.

[2294] Specific operation: The terminal provides an input interface, and after data is entered, pressing the send button sends the data to the server.

[2295] Step 2:

[2296] The terminal transmits the input data to the server.

[2297] Specific operation: The device sends data to the server via an HTTP request or API.

[2298] Step 3:

[2299] The server analyzes the received data using AI and monitors the health status.

[2300] What it does: The AI ​​analyzes the data, checks for any anomalies, and runs algorithms to assess whether it's within the normal range.

[2301] Step 4:

[2302] The server generates feedback for the user based on the analysis results and sends it to the device.

[2303] Specific operation: Analysis results and recommended actions are sent to the device in real time.

[2304] 4. Mental health support

[2305] Step 1:

[2306] The server periodically sends a stress check questionnaire to the terminal.

[2307] Specific operation: The server generates a stress check form and sends it to the terminal on the specified schedule.

[2308] Step 2:

[2309] The user answers the questionnaire and enters it into the terminal.

[2310] Specific operation: The terminal provides an interface for answering the survey questions and displays a button to submit the answers.

[2311] Step 3:

[2312] The terminal sends the questionnaire responses to the server.

[2313] Specific operation: Survey response data is sent to the server via HTTP request or API.

[2314] Step 4:

[2315] The server analyzes the response data using AI and evaluates stress levels.

[2316] What it does: The AI ​​analyzes your answers and runs an algorithm to quantify your stress level.

[2317] Step 5:

[2318] Based on the analysis results, the server suggests relaxation methods and sends them to the device.

[2319] Specific operation: Generate proposal content and send it to the terminal.

[2320] 5. Community Recommendations

[2321] Step 1:

[2322] The server recommends appropriate communities based on the user's profile.

[2323] Specific Operation: The server parses the profile information and generates a list of appropriate communities.

[2324] Step 2:

[2325] Users join recommended communities.

[2326] Specific operation: The terminal provides a participation interface and displays a participation button.

[2327] Step 3:

[2328] Users share information and experiences within the community.

[2329] Specific operation: The device provides messaging and posting functions to share information with other users.

[2330] 6. Memories storage

[2331] Step 1:

[2332] Users upload ultrasound images and photos of their child's growth record to the device.

[2333] Specific operation: The terminal provides a photo upload interface and sends the uploaded photos to the server.

[2334] Step 2:

[2335] The server analyzes the uploaded photos using facial recognition technology.

[2336] How it works: The AI ​​analyzes the photo data and runs an algorithm to identify important people in the photos.

[2337] Step 3:

[2338] The server selects important photos and generates an automatic album.

[2339] Specific operation: Organize photos chronologically and generate a digital album layout for the user.

[2340] Step 4:

[2341] The server transmits the generated album to the terminal.

[2342] Specific Actions: Create a digital album and provide a link for users to access it.

[2343] Example 1

[2344] 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."

[2345] Conventional information systems related to pregnancy, childbirth, and child-rearing only provide general information, making it difficult for individual users to obtain information and advice that is optimized for them. Furthermore, centralized management of health data and mental health support were insufficient, making it impossible to provide the comprehensive support that users need.

[2346] 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.

[2347] In this invention, the server includes a means for collecting user data, a means for generating information about pregnancy, childbirth, and child-rearing based on the collected data, and a means for distributing the generated information to the user. This enables personalized information and support. The system also includes a means for generating and providing personalized advice based on the user's questions, a means for managing, analyzing, and monitoring health data, a means for conducting and analyzing stress checks to support the user's mental health, and suggesting appropriate relaxation methods, a means for recommending online communities and allowing users to share information, and a means for analyzing uploaded images, selecting appropriate images, and generating a digital album. This allows users to receive comprehensive, personalized support, providing multifaceted support such as health management, mental health care, and promoting information sharing.

[2348] "User data" refers to data including profile information, health information, questions, etc. entered by the user.

[2349] "Information generation" is the process of generating information about pregnancy, childbirth, and parenting based on collected data.

[2350] "Information distribution" is the process of sending the generated information to the user's terminal and making it viewable.

[2351] "Personalized advice" is specific advice that is generated based on a user's individual questions and profile information.

[2352] "Health data management" is the process of collecting, analyzing, and monitoring user and child health information.

[2353] "Mental health support" is the process of conducting stress checks, analyzing stress levels, and suggesting appropriate relaxation methods to support the mental health of users.

[2354] "Online community recommendation" is the process of recommending appropriate communities based on a user's profile and encouraging them to join.

[2355] "Digital album generation" is the process of analyzing uploaded images, selecting important images, and creating a digital album.

[2356] "External data collection" is the process of obtaining data from external medical databases and research materials and storing it in an internal database.

[2357] "Personalized advice" refers to customized advice generated based on a user's profile information, health status, pregnancy stage, and health concerns.

[2358] MODE FOR CARRYING OUT THE INVENTION

[2359] This invention is a comprehensive system for providing information and support related to pregnancy, childbirth, and child-rearing, and utilizes AI technology to provide users with personalized information and advice. The purpose of this invention is to help users obtain the information they need in a timely and appropriate manner at each stage of their pregnancy and child-rearing lives.

[2360] 1. Collection of User Data

[2361] Users enter profile information such as age, number of weeks pregnant, health status, and past medical history into a device, which can be a smartphone, tablet, or PC.

[2362] The device sends the collected information to a server using a secure communication protocol (e.g., HTTPS).

[2363] The server validates the received data and stores it in a database, which can be an SQL database or a NoSQL database.

[2364] 2. Information Generation

[2365] The server periodically collects information from external medical databases (e.g., PubMed) and the latest research materials and stores them in an internal database.

[2366] AI models (e.g., GPT-3) analyze collected medical data and generate up-to-date information, including articles and advice on pregnancy, childbirth, and parenting.

[2367] 3. Information distribution

[2368] The server distributes the generated information to users, and in this process, the most appropriate information is selected based on each user's profile.

[2369] Users can access the information through an application or a web interface.

[2370] 4. Providing personalized advice

[2371] The user enters a specific question into the terminal and sends the question to the server.

[2372] The server uses AI to generate personalized advice based on the user's profile information and questions, and sends the answer to the device.

[2373] Example: When a user asks, "What can I do to prevent morning sickness?", the AI ​​will provide specific advice based on the user's number of weeks pregnant, such as "Diets that include ginger are effective."

[2374] 5. Health data management and monitoring

[2375] Users enter their daily health information (e.g., weight, body temperature, dietary details) into the device.

[2376] The terminal transmits this health information to the server.

[2377] The server uses AI to analyze the data and sends an alert if there is an abnormality.

[2378] Example: When a user enters their daily weight, the AI ​​analyzes changes in weight and, if there is a sudden increase, sends a warning to "consult a doctor."

[2379] 6. Mental health support

[2380] The server periodically sends a stress check questionnaire to the user's terminal.

[2381] The user answers the questionnaire and the results are sent to the server.

[2382] The AI ​​model will analyze the survey results and suggest relaxation and stress reduction methods as needed.

[2383] Example: If a user answers in a way that indicates high stress, the AI ​​will suggest "breathing techniques for relaxation."

[2384] 7. Community Recommendations

[2385] The server recommends appropriate online communities based on the user's profile.

[2386] Users join recommended communities and share information and experiences with other members.

[2387] Example: A new mother is recommended a "first-time parenting community."

[2388] 8. Photo analysis and album generation

[2389] Users upload ultrasound images and phot...

Claims

1. a means for collecting user data; A means of generating information about pregnancy, childbirth, and parenting based on the collected data; means for delivering the generated information to a user; means for generating and providing personalized advice based on a user's questions; A means to manage, analyze and monitor maternal and child health data; A method for conducting stress checks and analysis to support users' mental health and suggesting appropriate relaxation methods; It encourages communities and provides a means for users to share information with each other. means for analyzing the uploaded photos and selecting appropriate photos to generate an album; A system including:

2. 10. The system of claim 1, wherein data is collected from external medical databases and research papers and stored in an internal database.

3. The system of claim 1, wherein the system generates personalized advice based on the user's profile information, according to health status, pregnancy stage, and health issues.

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