Artificial intelligence-enabled Internet of Things-based system for COVID-19 screening using aerial thermal imaging

Abstract

\n Internet of Things (IoT) has recently brought an influential research and analysis platform in a broad diversity of academic and industrial disciplines, particularly in healthcare. The IoT revolution is reshaping current healthcare practices by consolidating technological, economic, and social views. Since December 2019, the spreading of COVID-19 across the world has impacted the world’s economy. IoT technology integrated with Artificial Intelligence (AI) can help address COVID-19. UAVs equipped with IoT devices produce raw data that demands computing analysis to make significant actions without human intervention. To mitigate the effect of COVID-19, in this paper, we design an IoT-UAV-based scheme that collects raw data using onboard thermal sensors. The thermal image captured from the thermal camera is used to determine the potential people in the image (of the massive crowd in a city), which might have COVID-19, based on the temperature recorded. An efficient hybrid approach for a face recognition system is proposed to detect the people in the image having high body temperature from infrared images captured in real-time. Also, a face mask detection scheme is introduced, which detects whether a person has a mask on the face or not. The schemes’ performance evaluation is done using various machine learning and deep learning classifiers. We use the edge computing infrastructure (onboard sensors and actuators) for data processing to reduce the response time and real-time analytics and prediction. The proposed approach delivers an average accuracy of \xa099.5% by using less than half the parameters for real-time predictions.\n