Leveraging Data Science in Cyber Physical Systems to Overcome Covid-19

As of July 2020, the total cases for the Novel Corona virus, Covid-19, peaked at a massive 12.3 Million victims, with over 550,000 casualties worldwide. In response to the staggering death rate and contagiousness of the disease, several disciplines of Cyber Physical Systems have provided heuristic solutions to flatten the curve and limit the rising cases per day. Big data analytics will act as a medium for tracking, controlling, research and prevention of COVID-19 as a pandemic. COVID-19 can be detected via information compiled using a framework for mobile phones. For Forecasting the time-series data, various DL methods are used to train data in the structured as well as unstructured format, with a biological information systems approach, to create knowledge platforms for research professionals. In order to carry out Detection of COVID-19, pre-trained models as well as customized Convolutional Neural Networks (CNNs) are trained using open-source CXR and CT scan image datasets, to compute their features. COVID-Net is a recent, publicly available, CNN-based model, used to detect COVID-19 in individuals, trained on a dataset of chest X-ray (CXR) images. Social Media can serve as a major source of relevant information on a daily basis. Researchers have conducted multiple studies related to social media analysis, tweets related to COVID-19 owing to the disease’s widespread nature.