Coronavirus Spread Limitation Using Detective Smart System

Abstract

Given the circumstances the world is going through due to the novel coronavirus (Covid-19); this paper proposes a new smart system that aims to reduce the spread of the virus. The proposed Covid-19 containment system is designed to be installed outside hospitals and medical centers. Additionally, it works at night as well as at daylight. The system is based on Deep Learning applied to pedestrian temperature data sets that are collected using thermal cameras. The data set is primarily of temperature of pedestrians around medical centers. The thermal cameras are paired with conventional cameras for image capturing and cross referencing the target pedestrian with an existing central database (Big Data). If target is positive, the system sends a text message to the potentially infected person's cell phone upon recognition. The advisory sent text may contain useful information such as the nearest testing or isolation facility. This proposed system is assumed to be linked with the bigger network of the country’s Covid-19 response efforts. The simulation results reveal that the system can achieve an average precision of 90% fever detection among pedestrians.