Smart Attendance Management System Using Face Recognition

Managing attendance in educational institutions is often a time-consuming and error-prone task, with traditional methods like roll calls or sign-in sheets being inefficient and susceptible to proxy attendance. This paper presents a Smart Attendance Management System that leverages facial recognition technology to automate the attendance process. By using cameras to capture images of students, the system recognizes their faces and marks their attendance in real time. Developed in Python, the system employs the K-Nearest Neighbours (KNN) algorithm for accurate face recognition. Once attendance is recorded, it is stored in a CSV file and can be visualized using the flask web application. The proposed system significantly reduces manual effort, ensures accuracy, and operates efficiently in real-time environments.

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Publication Details

Published
2025-02-21
DOI
https://doi.org/10.1109/ce2ct64011.2025.10941418
Primary Topic
Face recognition and analysis
Type
article
Field-Weighted Citation Impact
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article

Smart Attendance Management System Using Face Recognition

Nikita Rawat, Shivam Rawat, Shweta Goyal
Face recognition and analysis
article

Smart Attendance Management System Using Face Recognition

Nikita Rawat, Shivam Rawat, Shweta Goyal
article en

Abstract

Managing attendance in educational institutions is often a time-consuming and error-prone task, with traditional methods like roll calls or sign-in sheets being inefficient and susceptible to proxy attendance. This paper presents a Smart Attendance Management System that leverages facial recognition technology to automate the attendance process. By using cameras to capture images of students, the system recognizes their faces and marks their attendance in real time. Developed in Python, the system employs the K-Nearest Neighbours (KNN) algorithm for accurate face recognition. Once attendance is recorded, it is stored in a CSV file and can be visualized using the flask web application. The proposed system significantly reduces manual effort, ensures accuracy, and operates efficiently in real-time environments.

Graphic Era University (IN)
Openalex Percentile: Top 95%
Face recognition and analysis
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