Automated Attendance System with AI and Real-Time Camera Access using Facial Recognition

Abstract

The project focuses on developing an advanced attendance management system with deep learning and biometric technology to allow precise student attendance monitoring. The system works by providing live camera feeds for the clear photographic presentations of students when marked present and then going through with modern facial recognition algorithms out of a huge

database containing already registered students. The system marks the student's presence in nearly real-time manner, alerted by mail, SMS, or mobile applications whenever a positive match occurs. The system employs automation in this attendance- marking that reduces errors and the tiring workload associated with it. The teacher continuously receives information on present attendance trends on a macro or micro scale, which help them to spot any upward or downward trends in student engagement patterns with this information used for data-driven decision-making going forward. Besides that, it incorporates sufficient encryption and access mechanism, which guarantees the security and confidentiality of student records, thus rendering the solution genuinely reliable and efficient for just about any modern educational establishment. It boasts of features uniquely so geared in dynamic model training and update operations, which smoothly adjust to varying lighting condition changes and subsequently incorporate student appearance variation so as to guarantee a high level of accuracy and reliability. This new attendance system has great future use in educational institutions, offices, and other fields which consider attendance checking to be very important.