AttenTriX - student attendance application with geofencing and facial recognition

Most educators will spend a few minutes taking students’ attendance in the classroom, particularly in universities and colleges. It is possible to carry out this procedure in several ways, such as calling out students' names or giving them a piece of paper to sign as confirmation of attendance. This procedure is time-consuming, susceptible to fraud, and disruptive during class. This project aims to improve the attendance system to offer a more dependable and secure way to track students' attendance. Using the Convolutional Neural Network (CNN) algorithm, we examined the student's facial shape, eyes, nose, mouth, and other facial traits. The algorithm is used to build a model that can classify each student based on their face image. Moreover, geofencing detects and measures the student's location to determine whether the student is inside the classroom area.