Résumé
In December 2019, the SARS-CoV-2 virus, often referred to as COVID-19, was discovered in Wuhan, China. It is very virulent and has spread very quickly throughout the world. With COVID-19, people have described a wide variety of symptoms, from little discomfort to life-threatening respiratory illness. In this study, chest X-ray scan images are preprocessed using an anisotropic diffusion filter and three classifiers, and the Covid-19 cases are classified from the chest X-ray images using the GLRLM feature extraction approach. Common metrics like sensitivity, selectivity, and accuracy are utilized to compare the performance of the classifiers. When compared to other classifiers in this study, the Gaussian Mixture Model had the best accuracy of 91.07%. © 2022 IEEE.
Résumé
COVID-19 is an epidemic that has been multiplying rapidly across the globe. To order to regulate its growth, several nations have implemented home-stay or lockout policies. Prolonged domestic residency, though, can cause worse effects such as economic instability, homelessness, food shortages and individuals' mental health issues. This article presents an intelligent consumer electronics solution for secure & gradual launch after residence restrictions have been lifted. Completely automatic hand sanitizer supplier to prevent quickly spreading novel corona virus. It is implemented to restrict the development of new positive cases through auto touch tracking and by promoting critical social distancing.