Smart Captures- An Advanced Attendance System using Facial Recognition

Facial Recognition is one of the most productive and important techniques in image processing. It uses Machine Learning and Artificial Intelligence techniques to identify, collect, store, and evaluate face characteristics so that they can be matched to photos of people in a database. Nowadays, many kinds of research are focusing on human detection mainly in the context of marking students’ attendance. Marking attendance is a procedure of recognizing students’ faces and marking their attendance for that class. The need for this application was generated because after the pandemic use of touch biometric systems was suspended in many places and the manual process of taking attendance and maintaining paper records was a very tedious job and this could be manipulated very easily by anyone. Some attendance systems with face recognition already got developed but they were very basic and only had the feature of just recognizing the face once and marking the attendance of that student. So, by bringing in some unique features, here, developed ‘Smart Captures’, an advanced attendance system for universities, schools, and education-based places. Smart Captures was entitled to capturing the students’ movement from the classroom (in & out) and marking their attendance according to the set constraints using IoT, thereafter, making it visible to the faculties on their mobile application. This provided the data analytics for regular attendance on the dashboard to the admin with the administrative power using the application.