Automated Attendance Management System Using Face Recognition and GPS Localization

The evolving digital landscape in educational and organizational settings demands a robust and efficient method for attendance tracking.This paper presents an automated attendance management system that leverages state-of-the-art face recognition algorithms alongside GPS localization.The proposed system captures live facial images to extract unique biometric features and compares them against a pre-registered database for accurate identity verification.Concurrently, GPS data is used to ensure that attendance is recorded only when individuals are within a designated geographical boundary, effectively mitigating risks of proxy marking.Developed using Flutter for the user interface, Firebase for real-time backend processing, and Python-based recognition algorithms, the system has been designed for scalability and reliability.Experimental evaluations indicate that the integration of these technologies not only enhances the accuracy of attendance records but also reduces administrative overhead.The paper discusses the system architecture, methodological framework, implementation challenges, and potential improvements, paving the way for future research in automated attendance solutions.