Wi-Fi based student attendance recording system using logistic regression classification algorithm

Abstract

Monitoring students attendance is a crucial part of higher education. It has been established that students' attendance throughout the semester has positive correlations with their academic performances. The conventional method of recording atten- dance using a pen and paper is both time consuming and prone to cheating. Several technological solutions have been proposed to automate the attendance recording process, however, most of these solutions either high in cost, require additional hardware or prone to cheating. In this manuscript, we propose a new AI-based system that can automatically detect the student's presence or absence in a classroom using the Wi-Fi signal information collected from student's smartphone. The proposed system does not require any additional investment in hardware or infrastructure and achieves up to 94% accuracy by implementing the Logistic regression-based machine learning classification algorithm.