Low Computational Approach for Road Condition Monitoring Using Smartphones

Nowadays smartphone based sensing is becoming popular as the mobile sets are coming loaded with various kinds of sensors like camera, accelerometer, GPS, gyroscope, microphones etc. Smartphone based road condition monitoring is one of such useful application where built-in accelerometer is used to monitor road conditions. One issue in Smartphone based systems is battery power and hence there is need to look for low-computational complexity algorithms. In this paper, we propose such an approach using a small size (4 point) timewindowed analysis on low sampling rate (4 to 6 Hz) accelerometer data to detect road anomalies in real time as opposed to usual high sampling larger analysis point approaches (i.e. typically 25Hz to 500Hz sampling at 256 to 1000 points analysis window). This results in consuming less CPU cycles and in effect consuming less battery. Our approach focuses on the settling period of the vehicle vibration after it is hit by the road anomalies like potholes, bumpers etc. This allows us to work with very low sampling rate as the settling time of vehicles is in order of seconds in contrast to the actual impact time which lasts for only a fraction of seconds. Experimental results demonstrate the accuracy of low energy measurement approach with a detection resolution of two meters while keeping the computational complexity low. Keywords-Road monitoring, pothole detection, participatory