Comparison between artificial neural network and SPSS to predict vehicle emission

Abstract

Automobile is the chief pollutant among other sources of air pollution and it contributes more than half of the total pollution. The health hazards of air pollution are extremely dangerous and the most vulnerable persons are those using two wheelers, buses, and the pedestrians. Motor Vehicles are the chief constituents of the major pollutants like Oxides of Nitrogen, Carbon monoxide, Carbon dioxide, Hydrocarbon, and particulate matters through their tailpipe. The vehicles which runs through the fossil fuels are chief augmentation of the air pollution, which emits immense amount of nitrogen oxides in the air through their tailpipe. Emission from the cars are being the dominant source of pollutants, which emits about 36.5% of the total pollutants in Indian traffic scenario and about 75% of Carbon monoxide (CO) is due to automobile emission. Studies shows that automobile emissions are responsible for the major health hazards for humans and other living beings, this causes effects like cancer and other major health hazards like altered lung function, heart diseases, respiratory illness, eye irritation and asthma. The Literature reveals that car emission differs from different speed, age of the vehicle and other factors like acceleration, deceleration, idle condition, cruising condition and maintenance aspects. Speed of the vehicle and its relative position are calculated using GPS and the tailpipe emissions are quantified using five gas analysers and the vehicle maintenance data is collected from the vehicle user based on their frequency of service.. Study illustrates that tailpipe emissions like CO, HC and NOx are based on the speed of the vehicle and its age factors. From this study, we concluded that the tailpipe emission is falling off with raise in speed and after that the emission gradually gets escalated with raising the speed. The tail pipe emission data were collected by five gas analysers and the speed and location of the vehicle is determined by GPS under different driving conditions like static, acceleration, deceleration and cruising. The collected emission data are analysed by SPSS and ANN and the results shows that the emission rate goes on increasing with age of vehicle, speed and emission velocity.