Implementation of Covid-19 SARS Detection Method (CSDM) and Extended Simplified SIR Model (ESSM)
Abstract
In World, Most of the people upsetting about dangerous viruses, in that the primary disease are CoronaVirus Disease-19 (COVID-19) and most dangerous virus. As international concern Covid-19 can be treated as Emergency Public Health Issue (EPHI). It is a major contagious disease and easily infected one to hundreds of people within a couple of days. So that introduced Covid SARS Detection Method (CSDM) and Extended Simplified SIR Model (ESSM) are implement in MATLAB-Software. In CSDM Technique for collected sample human images affected by following symptoms like Difficulty Breathing, Fever and Cough etc then related to Real-Time-Image-Processing-Techniques (RTIPT). In CSDM Technique required fast processing time so that needed K-Means clustering algorithm, Support-Vector-Machine (SVM), Feature Extraction Algorithm (FEA) and Real-Time-Edge-Detection for identify the Corona Virus. Automatic identification and detection of Covid-19 disease is necessary to “Without Human Intervention” (WHI) identify those symptoms and signs as before as of initial phase. In ESSM Technique is essential for before prediction of Novel Covid-19 by extending of SIR Model. It is a complex mathematical model and epidemiological information. This can be useful to improvement of Medical Care Units (MCUs) and Intensive Care Units (ICUs).