A vehicular noise surveillance system integrated with vehicle type classification

This paper introduces an ongoing project on the surveillance of noisy vehicles on the road. Noise pollution created by vehicles on urban roads is becoming more severe. To enforce current measures, we developed a vehicular noise surveillance system including a vehicle type classification method. Samples of vehicular noise were recorded on-site using this system. Harmonic features were extracted from each sample based on an average harmonic structure. The k-nearest neighbor (KNN) algorithm was applied to achieve classification accuracies for the passenger car, the van, the lorry, the bus, and the motorbike of 60.66%, 65.38%, 52.99%, 62.02%, and 80%, respectively. This study was motivated by the demand of monitoring noise levels generated by different types of vehicles. The classification method using audio features is independent of lighting condition, thus providing a replacement to machine vision based techniques in vehicle type classification.