Sensor network based vehicle classification and license plate identification system

Conference · Thu Jan 01 00:00:00 EST 2009

DOI:https://doi.org/10.1109/INSS.2009.5409916· OSTI ID:956513

Frigo, Janette Rose ^[1]; Brennan, Sean M ^[1]; Rosten, Edward J ^[1]; Raby, Eric Y ^[1]; Kulathumani, Vinod K ^[2]

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1. Los Alamos National Laboratory
2. WEST VIRGINIA UNIV.

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.

• Research Organization: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC52-06NA25396
• OSTI ID: 956513
• Report Number(s): LA-UR-09-00256; LA-UR-09-256; TRN: US201014%%1882
• Resource Relation: Conference: INSS 2009 ; June 17, 2009 ; Pittsburgh, PA
• Country of Publication: United States
• Language: English

Related Subjects

99 GENERAL AND MISCELLANEOUS
ACOUSTICS
CAMERAS
CLASSIFICATION
DATA
DATA ACQUISITION SYSTEMS
DESIGN
ENERGY EFFICIENCY
IDENTIFICATION SYSTEMS
IMPLEMENTATION
LICENSES
MONITORING
PLATES
PROCESSING
SENSORS
SIGNALS
VEHICLES