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Wireless sensor networks (WSN) employ self-powered sensing devices that are mutually interconnected through wireless ad-hoc technologies. This study illustrates the basics of WSN-based traffic monitoring and summarises the possible benefits in Intelligent Transport Systems (ITS) applications for the improvement of quality and safety of mobility. Compared with conventional infrastructure-based monitoring systems, this technology facilitates a denser deployment of sensors along the road, resulting in a higher spatial resolution of traffic parameter sampling. An experimental data analysis reported in this study shows how the high spatial resolution can enhance the reliability of traffic modelling as well as the accuracy of short-term traffic state prediction. The analysis uses the data published by the freeway performance measurement system of the University of California-Berkeley and the California Department of Transportation. A microscopic cellular automata model is used to estimate traffic flow and occupancy over time on a road segment in which a relevant traffic-flow anomaly is detected. The analysis shows that the estimate accuracy improves for increasing number of active sensors, as feasible in the case of WSN-based monitoring systems.