Improving attendance tracking in tertiary institutions using automated face recognition and QR code technology

Abstract

This applied capstone project aims to improve attendance taking in tertiary institutions by creating an automated attendance system that uses face recognition and QR code technology. The system employs a two-step authentication process to mark students present, which makes it more difficult for dishonest students to bypass attendance tracking. The study found that the automated attendance system significantly simplified the attendance taking process and provided more accurate attendance data. However, the system's user interface could be improved, and it was only 73% accurate in identifying students correctly using face recognition, with masks and glasses hindering the identification process. Despite these limitations, the system has shown great potential for application in tertiary institutions such as Ashesi and other industries and institutions with minor modifications. This project provides an opportunity to replace inefficient traditional attendance methods with a more streamlined and competent solution