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Typically an Intelligent Transportation System (ITS) employs various types of infrastructure-based technologies into vehicles and roadways for monitoring traffic. But these solutions have high installation, maintenance, and operational costs. Further, most of these solutions are based on the assumptions of lane-based organized and homogeneous traffic, due to which these are ineffective in less organized traffic conditions which are common in developing countries. In this paper, we have proposed a cost-effective approach to infer the traffic state of the road by analyzing the cumulative acoustic signal collected from the microphone sensor of the user’s smartphone. To capture the distinctive characteristics of various traffic scenes, we explored two different types of features: Mel Frequency Cepstral Coefficients (MFCCs) and Wavelet Packet Transform (WPT). Based on the understanding of acoustic signals of different …