Smart attendance monitoring system using machine learning: A Review

Ingole Preeti, Wayal Sayali, Nanaware Payal * and B. H. Patil

Vidya Pratishthan’s Kamalnayan Bajaj Institute of Engineering and Technology, Baramati, India.
 
Review
World Journal of Advanced Engineering Technology and Sciences, 2024, 13(02), 022–025.
Article DOI: 10.30574/wjaets.2024.13.2.0504
Publication history: 
Received on 08 September 2024; revised on 18 October 2024; accepted on 21 October 2024
 
Abstract: 
This paper presents the development of a Smart Attendance Monitoring System using machine learning and face recognition technology to automate the process of tracking student attendance. The system uses cameras to capture student entry and exit times and logs this information in a dedicated application. By leveraging face recognition, the system identifies students and monitors how long they remain in the classroom. If a student stays for at least 30 minutes, their attendance is automatically marked as present. This approach eliminates manual attendance-taking, improves accuracy, and prevents proxy attendance, providing an efficient solution for educational institutions.
 
Keywords: 
Attendance Monitoring; Machine Learning; Face recognition; Open CV
 
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