Internet of Medical Things (IoMT) for Covid-19 Epidemic Affected People - Safdar, Zanab; Safdar, Kalsoom; Bajwa, Ruqia Safdar; Hussain, Shafiq; Karim, Ahmad (South Asian Journal of Social Sciences and Humanities, 2021)
i. Purpose of the study: Due to the rapid increase of COVID-19 cases, it has become challenging for the entire world to identify and treat infected patients at existing hospitals. In order to stop the spread of COVID-19, diseased persons need to be isolated for treatment. Hence, there is an enormous necessity to identify, monitor, and isolate patients to analyze their current situation and improve diagnostic accuracy to prevent more spread and deaths. ii. Methodology: Providentially, the recent advances in Information and communications technology (ICT) like the Internet of Medical Things (IoMT) bring us opportunities to win the battle against the COVID-19 crisis. The exploratory research distributes practical assistance to the researcher for the rudimentary work. In this study, the exploratory research method was executed to explore the existing literature intensively and recognize the COVID-19 affected patients’ issues or challenges. iii. Main Findings: A new approach of IoMT-based E-Health has been designed and proposed for affected patient’s treatment in real-time. IoMT based E-Health model venture a prodigious promise to treat isolated patients where it applies existing technologies to increase quality control and access to patient healthcare centers in this COVID-19 pandemic effectively. iv. Applications of this study: IoMT-based E-Health involves significant components to track, identify, monitor, manage, store, and analyze patient information for the ongoing COVID-19 pandemic. With the help of the proposed approach, existing hospitals and healthcare centers can manage many infected patients, suggest treatment, and respond quickly according to their emergency alerts. v. Novelty/Originality of this study: This study aims to identify current health systems’ challenges and design a specialized model for the IoMT based E-Health systems by focusing mainly on the challenges that surfaced during COVID-19.