IoMT based smart healthcare system to control outbreaks of the COVID-19 pandemic

Abstract

The COVID-19 pandemic caused millions of infections and deaths globally requiring effective solutions to fight the pandemic. The Internet of Things (IoT) provides data transmission without human intervention and thus mitigates infection chances. A road map is discussed in this study regarding the role of IoT applications to combat COVID-19. In addition, a real-time solution is provided to identify and monitor COVID-19 patients. The proposed framework comprises data collection using IoT-based devices, a health or quarantine center, a data warehouse for artificial intelligence (AI)-based analysis, and healthcare professionals to provide treatment. The efficacy of several machine learning models is also analyzed for the prediction of the severity level of COVID-19 patients using real-time IoT data and a dataset named 'COVID Symptoms Checker'. The proposed ensemble model combines random forest and extra tree classifiers using a soft voting criterion and achieves superior results with a 0.922 accuracy score. The use of IoT applications is found to support medical professionals in investigating the features of the contagious disease and support managing the COVID pandemic more efficiently.