Surveillance system for Mask detection using AI techniques

Abstract

2019 was the year of the most recent pandemic of COVID-19 which shocked global community. One of the best measures against the spreading of the disease was the use of mask in public spaces. In many of those public spaces monitoring the percentage of people wearing a mask can be implemented as an autonomous system using technologies from branches of Internet of things and Machine learning. Using live-feed from surveillance cameras to determine the percentages of people who wear and people who don’t is an interesting scientific problem due to its inherit difficulty in order to be real-time. The purpose of this thesis is to present an end to end system to solve this exact problem.