Next-Gen Attendance System: Face Recognition & Geolocation for Real-Time Employee Tracking

In recent years, facial recognition and geofencing have revolutionized attendance tracking systems, addressing the limitations of traditional methods like manual logbooks and RFID, which often suffer from inaccuracies and proxy attendance. This paper presents a mobile-based solution integrating Google ML Kit's face detection with a Convolutional Neural Network (CNN) for precise recognition and Google Maps API for geofencing. The system verifies attendance using facial recognition and real-time location data, ensuring secure identity validation. It uses a proprietary dataset of employee images and stores attendance records, including timestamps, in Firebase. Additionally, a manual check-in feature supports offsite employees with geolocation tracking. This hybrid approach enhances the accuracy, efficiency, and security of attendance tracking, catering to both in-office and remote work scenarios.