Implementation of Face Recognition Automated Attendance Management System using ESP32-CAM

Abstract: Attendance management is a crucial task in educational institutions and organizations. Traditional methods of recording attendance, such as manual entry or card-based systems, are time-consuming, error-prone, and difficult to manage in large-scale environments. To overcome these challenges, this paper presents an automated attendance management system using the ESP32-CAM microcontroller integrated with face recognition technology. The system captures real-time images, processes them using a Haar Cascade Classifier for face detection, and employs Principal Component Analysis (PCA) for face recognition. Upon successful recognition, the system automatically logs the attendance into a centralized database. The ESP32- CAM’s low cost, compact size, and wireless connectivity make it an ideal solution for large-scale deployment. The proposed system achieved an accuracy of approximately 95% with a low false positive rate, demonstrating reliable performance even under varying lighting conditions. This solution reduces human effort, improves accuracy, and ensures real-time attendance monitoring, making it suitable for educational institutions and professional environments