Eluding Soot for Better Environment Using Machine Learning

Abstract

Environment is getting polluted from the harmful gases released by the vehicles which leads to many lung disorders in human beings and also depletes ozone layer which surrounds the earth. This paper explains avoiding those problems by following instructions and information technology. Road transport is one of biggest sources of pollution in the world, out of the 80 million vehicles on our road, 59% are diesel vehicles. Diesel vehicles emit higher levels of NOx and much higher emission of particulate matter, to control the emission of toxic pollutants from the diesel vehicles, when a vehicle arrives at the gas station and the license plate of vehicle scan using OCR technology, and verifies the emission test update by comparing vehicle data in centralized hub (Core FTP lite server). And RC card value input to verify emission test too.  Buzzer triggering based on decision tree to ensure the result of emission test, negative result failed to get gas, if positive procedure should be followed. And two-way authentication using RFID technology, Result shows that the proposed system is superior in performance with 95% accuracy and is highly effective, robust and reliable in delivering to our environment can be identified and thereby controlling air pollution.