Year: 2025
Type: article
Abstract: Education institutions together with workplaces need attendance management systems to maintain order and record workforce participation. Traditional attendance processes which blend manual marking with RFID systems are inefficient as well as time-consuming and are easily susceptible to attendance fraud by proxy members. We propose building an automatic attendance tracking system through Face Recognition Attendance System that relies on OpenCV and MTCNN modules. The system operates with real-time video through a camera to recognize faces which are then preprocessed prior to matching them against registered user records stored in the system database. The system compares captured data against its database and registers attendance in the MySQL database which enables efficient storage and retrieval. A smooth user interface results from the system's implementation with a React.js frontend and Flask backend structure. The system implements Twilio API integration which provides immediate alerts to students along with administrators. Through the proposed system institutions enhance the accuracy of attendance records as they automatically track attendance while providing security benefits. The system shows excellent performance according to experimental tests that confirm its reliability for automatic attendance tracking under different lighting scenarios.
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4409205072