IoT-Enhanced Smart Attendance System by Integrating Mobile Application, NodeMCU ESP8266, Computer Vision

A complete smart attendance system incorporates the usage of IoT technology, biometric authentication, and facial recognition to improve efficiency, security, and accuracy for processes of tracking attendance in academic institutions. It uses a three-level authenticating framework, which is unique and comprises validation of WiFi connectivity, fingerprint biometric verification, and facial recognition and affords highly secure processes of attendance. A NodeMCU ESP8266 microcontroller establishes a localized WiFi network, thereby limiting the application to only users who are physically present on campus premises. Further security is enhanced by a Flutter-based mobile application that requires fingerprint authentication for authorized access. The app captures the image of the user, which is transmitted to a Python Flask server for facial recognition verification. The attendance data is verified and stored in a MySQL database and then monitored with a real-time admin dashboard built using React. The multi-level security approach ensures that the system eliminates long queues for marking attendance and the problem of buddy punching. Experimental evaluations and test results prove that the system is reliable and effective in the reduction of manual errors, improvement of operational efficiency, and offering a scalable solution to academic institutions.