Journal of Management Information and Decision Sciences (Print ISSN: 1524-7252; Online ISSN: 1532-5806)


Implementation of Covid-19 Monitoring Systems Using Machine Learning Algorithms in Edge Networks.

Author(s): Syefy Mohammed Mangj Al-Razoky, Payman Hussein Hussan & Hasanain Mohammed Manji Al-Rzoky

The Corona Virus is a new viral infection that has brought a catastrophic outbreak in the world. The pandemic has caused all the people to face a new threat. Everyone and almost every healthcare organisation are putting their best efforts to deal with and fight against the epidemic. The researchers of Artificial Intelligence are now focusing on experimenting with new ways from their expertise to build Machine Learning models for examining the Covid-19 outbreak by using worldwide collected data. The well-being of a society is now one of the important priorities of these researchers and for that, they are going to analyse this data to make everyone more cautious to deal with the pandemic situation. This article proposes to make use of Machine Learning Algorithms to recognize its day-to-day exponential behavior together with the detection and prediction of the future possibility of Coronavirus outbreak across the world. The article suggests that for such detection and prediction real-time information is needed to develop the ML algorithms. The research suggests eight ML algorithms for quick detection of suspected Covid cases. The findings of the study discusses how various researchers attempted to develop ML technologies to provide required information to infected patients and also provide help to healthcare sectors. Some researchers are also focused on developing exploratory data analysis to collect information such as the number of the Covid cases, deaths, and recoveries to prepare new strategies and activity for future threats. The research has been developed by forming secondary qualitative and quantitative data and for that graphs and table has been generated
Get the App