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VOL. 10, ISSUE 3 (2025)
A study on AI-based automated attendance systems using face recognition in schools and colleges
Authors
Prakash Balasaheb Mande, Sanchita Sunil Waman
Abstract
Artificial Intelligence (AI)-based automated
attendance systems utilizing face recognition technology are transforming
traditional attendance tracking methods in schools and colleges by enhancing
efficiency, accuracy, and security. This study explores the development and
implementation of an AI-driven facial recognition system designed to automate
attendance marking, reducing manual errors and preventing proxy attendance. The
proposed system employs deep learning algorithms, such as Convolutional Neural
Networks (CNNs), for facial feature extraction and recognition, ensuring high
accuracy even in varying lighting conditions and diverse student demographics.
By integrating cloud-based databases and realtime image processing, the system
enables seamless attendance management while maintaining data privacy and
security. Additionally, this research evaluates the performance of different
face recognition models, comparing factors like recognition speed, accuracy, and
computational efficiency. The adoption of AI-powered attendance systems in
educational institutions not only minimizes administrative workload but also
improves classroom discipline and attendance monitoring. Furthermore, this
paper discusses potential challenges, including ethical concerns, data
security, and system bias, proposing solutions to enhance fairness and
reliability. The findings suggest that AIdriven face recognition technology
offers a scalable and effective alternative to conventional attendance systems,
paving the way for smarter, tech-enabled education environments.
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Pages:116-120
How to cite this article:
Prakash Balasaheb Mande, Sanchita Sunil Waman "A study on AI-based automated attendance systems using face recognition in schools and colleges". International Journal of Advanced Scientific Research, Vol 10, Issue 3, 2025, Pages 116-120
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