AttendIQ: A Web-Based Contactless Academic Attendance System Using Machine Learning Algorithm

AttendIQ addresses the limitations of conventional attendance management comprehensively by integrating real-time face recognition with a full-featured, role-based web management portal. The system's three-tier architecture — Administrator, Teacher, and Student — ensures each stakeholder group has precisely the tools required for their responsibilities. The Flask backend, React.js frontend, and SQLite database form a cohesive, deployable technical stack appropriate for institutional-scale academic management.   Key contributions include the two-level anti-proxy mechanism, session-anchored manual correction, comprehensive academic lifecycle management across eight semesters, multi-tenant architecture, and integrated attendance analytics with PDF export. Experimental results confirmed 100% accuracy in role-based access control, ~94% face recognition accuracy, and correct anti-proxy detection in all tested scenarios. While limitations including plaintext password storage and absence of liveness detection require remediation before production deployment, the modular architecture readily accommodates these enhancements. AttendIQ represents a meaningful step toward modernization of academic attendance management.  

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