Authors: Vishal Kumar Pandey, Vishal Jaiswal, Vishal Yadav, Shilpee Patil
Abstract: Classroom attendance tracking was a fundamental task in educational institutions, traditionally managed through manual roll calls or sign-in sheets. These methods were time-consuming, error-prone, and susceptible to manipulation. With advancements in computer vision and embedded systems, there was an opportunity to automate this process. In this research paper, a novel approach to classroom attendance management was presented, utilizing OpenCV and face recognition technologies, implemented on the ESP32-CAM microcontroller. The proposed system was designed to automatically identify and record student attendance, offering enhanced accuracy and efficiency. Comparative results demonstrated that the face recognition-based approach significantly outperformed traditional manual methods and other automated systems in terms of accuracy and processing speed. The system's architecture, implementation, and evaluation were outlined, showcasing its potential to transform attendance tracking in educational settings.
DOI: https://doi.org/10.5281/zenodo.16410064
