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My graduation thesis project, awarded a 9.5/10, involved creating a student attendance management system for iOS devices that utilizes FaceNet facial recognition model for efficient and secure attendance tracking.

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huypham85/facenet-recognization-ios

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Class Attendance App

Project Overview

This project involves the development of a student attendance management system for iOS devices. The system leverages the FaceNet facial recognition model and Bluetooth Low Energy (BLE) technology to ensure efficient, secure, and reliable attendance tracking.

Features

  • Facial Recognition: Utilizes the FaceNet model for accurate facial identification.
  • Bluetooth Low Energy (BLE): Ensures students are within close proximity to the teacher's device for attendance check-in.
  • iOS Application: User-friendly app for both students and teachers to manage attendance.
  • Admin Web Interface: Web platform for admin to manage classes, users, and approve face registration requests.

Key Technologies

  • FaceNet: Facial recognition model developed by Google.
  • BLE (Bluetooth Low Energy): Ensures proximity between devices for attendance check-in.
  • Firebase: Backend services for real-time database, authentication, and storage.
  • iOS Development: UIKit, Swift.
  • Machine Learning: Pre-trained model for facial recognition.

Key Achievements

  • High Accuracy: The system identifies students with approximately 95% accuracy.
  • Fast Processing: Attendance check-in takes around 0.25 seconds per student.
  • Flexible Check-In: Students can check in via their own devices, increasing convenience and reducing the need for a fixed check-in device.

How to Use

  1. Register: Students and teachers need to register and get approval for their facial data.
  2. Check-In: Students can check in to their classes by simply being in close proximity to the teacher's device and having their face recognized by the app.

Setup and Installation

Prerequisites

  • Xcode: Version 11 or later.
  • Swift: Version 5.1 or later.
  • Cocoapods: To manage dependencies.

Installation

  1. Clone the repository:

    git clone https://github.com/yourusername/class-attendance-app.git
    cd class-attendance-app
  2. Install dependencies:

    pod install
  3. Open the project in Xcode:

    open ClassAttendanceApp.xcworkspace
  4. Build and run the project: Select your target device or simulator and press Cmd + R to build and run the project.

Usage

  1. Register and Login:

    • Open the app and register as a student or teacher.
    • Admin will approve the registration request.
  2. Face Registration:

    • Take a clear picture of your face for recognition.
    • Admin will approve the face registration.
  3. Attendance Check-In:

    • Open the app and ensure you are close to the teacher’s device.
    • The app will automatically recognize your face and mark your attendance.

Architecture

iOS App

  • UIKit: For building the user interface.
  • FaceNet: For facial recognition.
  • BLE: For proximity detection.
  • Firebase: For real-time database, authentication, and storage.

Admin Web Interface

  • React: For building the web interface.
  • Firebase: For backend services.

Screenshots

Picture1 Picture2 Picture3 Picture4 Picture5 Picture6 Picture7 Picture8

Contribution

Contributions are welcome! Please follow these steps:

  1. Fork the repository.
  2. Create a new branch:
    git checkout -b feature-branch
  3. Make your changes and commit them:
    git commit -m "Description of your changes"
  4. Push to the branch:
    git push origin feature-branch
  5. Create a pull request.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Acknowledgments

Special thanks to all contributors and the developer community for their valuable feedback and contributions.

About

My graduation thesis project, awarded a 9.5/10, involved creating a student attendance management system for iOS devices that utilizes FaceNet facial recognition model for efficient and secure attendance tracking.

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