Facial Recognition for Automated Attendance Management: A Solution Adapted to Senegalese Educational Environments

This research proposes an automated attendance management solution using facial recognition, tailored to the Senegalese educational system. Given the challenges of traditional methods in overcrowded classrooms, our approach integrates artificial intelligence through the OpenCV DNN module, providing a balance between accuracy and required resources. The developed architecture combines an intuitive user interface, realtime video processing, and automated report generation, relying on a Flask server and a MySQL database. The solution is adapted to local constraints, particularly ethnic diversity, and integrates with existing surveillance systems. Tests demonstrate high facial detection accuracy while respecting ethical considerations and complying with Senegalese legal frameworks for personal data protection, thus contributing to the modernization of the educational system.