Dynamic attendance system using face recognition via machine learning models

<p>Traditional <span lang="EN-US">methods to handle attendance have been implemented in the schools in the past and most of them are discouraging as they require that the institutions implement the use of paper and pen to get the results. To enhancing effectiveness and safeguarding, this paper presents a face recognition attendance system that mechanizes the usual attendance taking process. Using best practices in facial recognition, the system captures images of students’ faces, stores them, feeds them into a recognition model, and uses real-time facial recognition to mark attendance. This means that the system enjoys data encryption and password protected access that ensures data is safe. In the proposed system, the OpenCV face recognition libraries combined with machine learning algorithms for better face recognition ability with better efficiency. The results confirm that the system provides a reliable approach to handling attendance and it may debut in various contexts.</span></p>

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Publication Details

Journal
Indonesian Journal of Electrical Engineering and Computer Science
Published
2025-08-01
DOI
https://doi.org/10.11591/ijeecs.v39.i2.pp1421-1430
Primary Topic
Face recognition and analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

Dynamic attendance system using face recognition via machine learning models

Sanjeev Kumar, Nidhi Bansal, Harshit Harshit, Емил Велинов et al.
Indonesian Journal of Electrical Engineering and Computer Science
Face recognition and analysis
article

Dynamic attendance system using face recognition via machine learning models

Sanjeev Kumar, Nidhi Bansal, Harshit Harshit, Емил Велинов, Nishant Upadhyay, Abhay Sharma
article en

Abstract

<p>Traditional <span lang="EN-US">methods to handle attendance have been implemented in the schools in the past and most of them are discouraging as they require that the institutions implement the use of paper and pen to get the results. To enhancing effectiveness and safeguarding, this paper presents a face recognition attendance system that mechanizes the usual attendance taking process. Using best practices in facial recognition, the system captures images of students’ faces, stores them, feeds them into a recognition model, and uses real-time facial recognition to mark attendance. This means that the system enjoys data encryption and password protected access that ensures data is safe. In the proposed system, the OpenCV face recognition libraries combined with machine learning algorithms for better face recognition ability with better efficiency. The results confirm that the system provides a reliable approach to handling attendance and it may debut in various contexts.</span></p>

Indonesian Journal of Electrical Engineering and Computer ScienceVol. 39(2)
Lovely Professional University (IN), RISEBA University of Applied Sciences (LV), Manav Rachna International Institute of Research and Studies (IN), Manipal University Jaipur, Sharda University (IN)
Openalex Percentile: Top 81%
Face recognition and analysis
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Dynamic attendance system using face recognition via machine learning models — Sanjeev Kumar, Nidhi Bansal, et al. · Indonesian Journal of Electrical Engineering and Computer Science (2025) | TGRS Research Map | TGRS