Researchers at the Indian Institute of Technology, Madras (IIT-M) have developed a “real-time exhaust emission prediction model,” stated to be for the first time, that can help manage urban air quality and aid traffic planning in India.
Imagine a mobile app flashing emission levels of your car in real time, helping you to make necessary changes in driving, assisting policy makers in managing grid-wise traffic flow, indicating roads that register the highest pollution levels and warrant traffic decongestion, besides improving the Indian emission standards. IIT-M Ph.D student Rohit Jaykumar, who developed the model, claims that all this can be realised with the artificial neural network (ANN)-based new prediction model.
A sample study was conducted using 10 different diesel passenger cars under different traffic conditions to measure three pollutants, including nitrogen oxide (NOX), carbon monoxide (CO) and hydrocarbons (HC). Sardar Patel Road (3.2 km), which has four lanes, and the two-lane Velachery Main Road (4.4 km) were used for the testing. Separate software was indigenously developed to sync onboard diagnostics (OBD) port in the vehicles and ARAI certified AVL Digas analyzer, which can record emissions at 1 Hz under real-world operating conditions.
“The results were astonishing. The vehicular emissions were 25 times higher than conventional predictions,” Jaykumar said and added that he had now widened the scope of study to test the model for different types of vehicles.
Read the full article @ Times of India
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