Automated Attendance System Using Facial Recognition: A Comprehensive Review

Abstract

In contemporary settings, attendance tracking serves as a fundamental aspect across various domains, including educational institutions and corporate environments. Traditionally reliant on manual methods, the cumbersome nature of these processes has prompted a paradigm shift towards more innovative and automated solutions. The emergence of Facial Recognition Technology (FRT) has garnered significant attention as a potential game-changer in this landscape. This review paper delves into the historical evolution and intricate technological facets of automated attendance systems utilizing facial recognition. From a chronological perspective, we explore the trajectory of these systems, outlining their transformative journey from nascent experiments to sophisticated, real-world applications. Key considerations include the underlying algorithms, sensor technologies, and their collective role in shaping the current state of FRT-based attendance tracking. As we navigate the literature, a comprehensive comparative analysis uncovers the strengths and weaknesses of existing facial recognition-based attendance systems. By critically evaluating their performance against traditional methods, we discern the nuanced intricacies that underscore the efficacy of these systems in diverse contexts. Moreover, a meticulous examination of challenges, ranging from privacy concerns to environmental factors, offers insights into the limitations currently inhibiting the widespread adoption of FRT. The review culminates in a forward-looking exploration of the future scope, pinpointing potential breakthroughs and areas for optimization. This paper aims to contribute valuable perspectives to researchers, practitioners, and policymakers alike, providing a holistic understanding of the present landscape and envisioning the trajectory of facial recognition technology in revolutionizing attendance tracking.

Topics & Concepts