CerebrAI: Smartphone-Based Facial Recognition for Classroom Attendance

Attendance tracking is a critical process in many places like educational institutions and professional workplaces, but traditional methods like paper-based records and RFID systems are still being used, which are vulnerable to manipulation, errors and inefficiencies. This paper presents CerebrAI, a mobilebased facial recognition system to automate attendance recording in real time, which was developed in collaboration with King Mongkut’s University of Technology Thonburi (KMUTT). The system is designed to be cost-effective, accurate and intuitive, allowing lecturers to record student attendance without the need for expensive external hardware. Implemented using Flutter, Dart, face-recognition library, OpenCV library and a MySQL database, CerebrAI detects and verifies faces, stores attendances and provides administrators with backup functionalities. To ensure data integrity and privacy, students are unable to modify the records. By eliminating manual processes and reducing reliance on costly biometric devices, this solution showcases the feasibility of deploying AI-based attendance systems using affordable devices such as smartphones, with potential applications in broader institutional contexts.