Detection and Tracking Contagion using IoT-Edge Technologies: Confronting COVID-19 Pandemic
Muhammad Usman Ashraf, Abdul Hannan, Sehrish Munawar Cheema, Zahra Ali, Kamal Jambi, Abdulraheem Alofi
Abstract
The ongoing pandemic of Corona-Virus (COVID-19) induced by the coming forth category of SARS-CoV-2, has terrified the worldwide human health. Primarily, COVID-19 challenges can be categorized into (a) way of epidemic prevention and blocking transmission, (b) live monitoring of infected / suspected persons (c) FDA approved vaccine. Leading to said COVID-19 (a), (b) challenges, digit technologies such Artificial Intelligence, Big data analytics and Internet of Things (IoT), can play a vital role in epidemic prevention and blocking COVID-19 transmission. In this study, we have proposed a smart edge surveillance system that is effective in remote monitoring, advance warning and detection of a person's fever, heart beat rate, cardiac conditions and some of the radiological features to detect the infected (suspicious) person using wearable smart gadgets. The proposed framework provides a continually updated map/pattern of communication chain of COVID-19 infected persons that may span around in our national community. The health and societal impact of suggested research is to help public health authorities, researchers and clinicians contain and manage this disease through smart edge surveillance systems. The proposed model will help to detect and track the contagious person. Moreover, it will also keep the patient's data record for analysis and decision making using edge computing.