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ISSN: 2582-8266 (Online)  || UGC Compliant Journal || Google Indexed || Impact Factor: 9.48 || Crossref DOI

Fast Publication within 2 days || Low Article Processing charges || Peer reviewed and Referred Journal

Research and review articles are invited for publication in Volume 18, Issue 2 (February 2026).... Submit articles

Smart attendance monitoring system using machine learning: A Review

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  • 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 Article
 
World Journal of Advanced Engineering Technology and Sciences, 2024, 13(02), 022–025.
Article DOI: 10.30574/wjaets.2024.13.2.0504
DOI url: https://doi.org/10.30574/wjaets.2024.13.2.0504

Received on 08 September 2024; revised on 18 October 2024; accepted on 21 October 2024

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.

Attendance Monitoring; Machine Learning; Face recognition; Open CV

https://wjaets.com/sites/default/files/fulltext_pdf/WJAETS-2024-0504.pdf

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Ingole Preeti, Wayal Sayali, Nanaware Payal and B. H. Patil. Smart attendance monitoring system using machine learning: A Review. World Journal of Advanced Engineering Technology and Sciences, 2024, 13(02), 022–025. Article DOI: https://doi.org/10.30574/wjaets.2024.13.2.0504

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