Abstract: Existing traffic information acquisition systems suffer from high cost and low
scalability. To address these problems, the application of wireless sensor networks (WSNs)
has been studied, as WSN-based systems are highly scalable and have a low cost of
installing and replacing the systems. Magnetic, acoustic and accelerometer sensors have
been considered for WSN-based traffic surveillance, but the use of ultrasonic sensors has
not been studied. The limitations of WSN-based systems make it necessary to employ
power saving methods and vehicle detection algorithms with low computational
complexity. In this paper, we model and analyze optimal power saving methodologies for
an ultrasonic sensor and present a computationally-efficient vehicle detection algorithm
using ultrasonic data. The proposed methodologies are implemented and evaluated with a
tiny microprocessor on real roads. The evaluation results show that the low computational
complexity of our algorithm does not compromise the accuracy of vehicle detection.