Schematized study for tackling COVID-19 with Machine Learning (ML), Artificial Intelligence (AI), and Internet of Things (IoT)

Abstract

The novel Coronavirus (COVID-19) is caused by the newly identified strain of the coronavirus family severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), whose target organ is the lungs. It has become a global pandemic, and COVID-19 poses so far unprecedented challenges to healthcare systems around the globe, particularly to those with weakened immune systems. Effective methods for managing, diagnosing, and lessening the effects of COVID-19 are critical because, by 2024, the virus has already caused over 7 million deaths. In this study, we anatomize the impacts of the latest COVID-19 virus on patients with the help of computational intelligence, like Machine learning, artificial intelligence, and IoT-enabled technologies for managing, analyzing, diagnosing, and predicting COVID-19. With tools for early identification, risk assessment, and therapy optimization, machine learning and artificial intelligence have shown tremendous promise in the healthcare industry. These tools can examine big datasets to find patterns and trends that might not be noticeable to human observers. Additionally, IoT will enable healthcare firms to monitor patient scenarios properly and reduce the readmission of COVID-19 patients. Wearable sensors and remote monitoring systems are two examples of IoT-enabled gadgets that are vital for tracking the COVID-19 virus's spread and keeping an eye on its sufferers. These gadgets can gather data in real-time on environmental variables, symptoms, and vital signs, giving medical professionals important insights into the state of their patients' health and the course of their diseases. This study will play a vital role in competing for safety considerations of reducing SARS-CoV-2, COVID-19, and exposure with the assistance of smart technology and provide much-needed information regarding the impact of COVID-19 on patients that will benefit globally.