Open AccessFuzzy Logic Inference System for Identification and Prevention of Coronavirus (COVID-19)
Author(s) -
Manoj Sharma,
Nitesh Dhiman
Publication year - 2020
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.f4642.049620
Subject(s) - covid-19 , coronavirus , pandemic , identification (biology) , fuzzy logic , fuzzy inference system , inference , virology , computer science , fuzzy control system , environmental health , artificial intelligence , medicine , adaptive neuro fuzzy inference system , disease , biology , infectious disease (medical specialty) , ecology , outbreak
Now a days Novel Coronavirus named COVID-19 becomes major health concern causing severe health issue in human beings and it becomes a pandemic. It’s a kind of zoonotic that means it can transmit animals to humans. It may spread via polluted hands or metals. No specific treatment is available so far for COVID-19, so initial identification and preventions for COVID-19 will be crucial to control or to break down the chain of COVID-19. For this purpose, we have proposed a fuzzy inference system to diagnose the COVID-19 disease by taking six input factor like as; Ethanol, Atmospheric Temperature (AT), Body Temperature (BT), Breath Shortness (BS), Cough and Cold and the output factor has divided into three linguistic categories which denotes the severity level of the infected patients.