Smart Attendance System Using Ai-Driven Face Recognition

ABSTRACT In modern educational environments, maintaining accurate and efficient attendance records is vital for monitoring student participation, discipline, and academic progress. Traditional methods such as manual roll calls or paper registers are time-consuming, error-prone, and susceptible to proxy attendance, leading to inefficiencies in large classrooms. Existing digital approaches, including RFID and biometric fingerprint systems, have improved accuracy but face challenges related to cost, scalability, and hygiene. To address these limitations, this research proposes a Smart Attendance System based on Artificial Intelligence (AI) and Computer Vision, utilizing face recognition technology for contactless and automated attendance marking. The system employs lightweight frameworks such as face-api.js to perform real-time recognition directly within the browser, eliminating the need for expensive hardware or dedicated servers. It supports student enrollment through multi-angle facial image captures and leverages cosine or Euclidean distance-based comparisons for identity verification. The proposed approach ensures higher accuracy, enhanced efficiency, and scalability, making it a cost-effective solution for modern educational institutions seeking digital transformation.