COVID-X: Novel Health-Fog Framework Based on Neutrosophic Classifier for Confrontation Covid-19

Abstract

The newly identified Coronavirus pneumonia, subsequently termed COVID-19, is highly
transmittable and pathogenic with no clinically approved antiviral drug or vaccine available for
treatment. Technological developments like edge computing, fog computing, Internet of Things
(IoT), and Big Data have gained importance due to their robustness and ability to provide diverse
response characteristics based on target application. In this paper, we present a novel Health-Fog
framework universal system to automatically assist the early diagnosis, treatment, and preventive
of people with COVID-19 in an efficient manner. Achieving an empirical of the proposed framework
which mix between deep learning and Neutrosophic classifiers in the task of classifying COVID-19.
There are some proposed applications based on the proposed COVID-X framework such as smart
mask, smart medical suit, safe spacer, and Medical Mobile Learning (MML) will be presented.
Computer-aided diagnosis systems could assist in the early detection of COVID-19 abnormalities
and help to monitor the progression of the disease, potentially reduce mortality rates.