Effective Screening and Face Mask Detection for COVID Spread Mitigation Using Deep Learning and Edge Devices

Abstract

The emergence of COVID-19, stemming from the SARS-CoV-2 virus, has led to a widespread outbreak affecting countless individuals and inducing dire circumstances globally. Mitigating the transmission of COVID-19 has necessitated the implementation of effective measures such as rigorous COVID screening and physical safeguards, including practices like social distancing and the utilization of face masks. Notably, the application of advanced technologies such as deep learning, a subset of artificial intelligence (AI), has played a pivotal role in devising novel strategies for both detecting COVID-19 and curbing its propagation. This chapter presents a comprehensive overview of COVID screening methodologies based on deep learning, with a specific focus on biomedical image processing and the detection of face masks. Furthermore, it delves into initial endeavors concerning COVID image analysis and the creation of a mobile face mask detection system, designed to operate on edge devices. The ensuing discussions encompass detailed case studies, showcasing the practical implications and efficacy of these initiatives.