Fingerprint-Based Automated Student Attendance Monitoring and Analytics System

This paper presents the design and implementation of an entry-exit fingerprint-based attendance system using an ESP32 microcontroller.The system replaces manual roll calls with biometric verification, uniquely identifying each student via fingerprint at both the start and end of a lecture.A single 5 V regulated supply powers all components, including the fingerprint sensor, ESP32, and LCD display.When a student scans at entry and exit, the ESP32 records each timestamp and transmits attendance data wirelessly via built-in Wi-Fi to a cloud database.A real-time cloud dashboard allows teachers to monitor attendance and run analytics on attendance rates.Entry-exit logic ensures that only students who attend the full lecture are marked present, effectively preventing proxy or partial attendance.In tests, the system achieved reliable fingerprint recognition approximately 95% recognition accuracy under controlled classroom testing with enrolled users and real-time reporting of attendance, demonstrating efficiency gains over manual methods.