Facial Recognition System for Efficient Attendance Monitoring using LBPH Classifier Algorithm

A clever and dependable solution for real-time attendance tracking in educational institutions isoffered by the proposed project, "Facial Recognition System for Efficient Attendance Monitoring usingLBPH Classifier Algorithm." With role-based access, administrators and students can both log in to thissystem. Through face recognition, students can easily check in and out and register their facial data,guaranteeing a contactless and secure way to record attendance. Features that let administrators createthorough attendance reports based on particular date ranges or student names are available to them. Theycan also register student faces. Through the use of an interactive Power BI Dashboard, students can alsoexamine their own attendance records by choosing a custom time frame and use a graphical representationto assess their presence at the school. In addition, the system is set up to notify students via email as soon asthey check in or out, giving them real-time information. Along with removing manual errors and fosteringdigital transformation in educational settings, the system enhances the precision, security, and effectivenessof attendance tracking by fusing facial recognition technology with data visualization and notificationcapabilities.