Sensor network based vehicle classification and license plate identification system

Authors:
Jan Frigo;Vinod Kulathumani;Sean Brennan;Ed Rosten;Eric Raby
Affiliations:
Distributed Sensor Networks Group, Los Alamos National Labs;Dept. of Computer Science and Electrical Engineering, West Virginia University;Distributed Sensor Networks Group, Los Alamos National Labs;Dept. of Engineering, University of Cambridge;Distributed Sensor Networks Group, Los Alamos National Labs
Venue:
INSS'09 Proceedings of the 6th international conference on Networked sensing systems
Year:
2009

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Abstract

Typically, for energy efficiency and scalability purposes, sensor networks have been used in the context of environmental and traffic monitoring applications in which operations at the sensor level are not computationally intensive. But increasingly, sensor network applications require data and compute intensive sensors such video cameras and microphones. In this paper, we describe the design and implementation of two such systems: a vehicle classifier based on acoustic signals and a license plate identification system using a camera. The systems are implemented in an energy-efficient manner to the extent possible using commercially available hardware, the Mica motes and the Stargate platform. Our experience in designing these systems leads us to consider an alternate more flexible, modular, low-power mote architecture that uses a combination of FPGAs, specialized embedded processing units and sensor data acquisition systems.