Monitoring Systems White Papers
Lightweight Detection and Classification for Wireless Sensor Networks in Realistic Environments
Overview A wide variety of sensors have been incorporated into a spectrum of Wireless Sensor Network (WSN) platforms, providing flexible sensing capability over a large number of low-power and inexpensive nodes. Traditional signal processing algorithms, however, often prove too complex for energy-and-cost-effective WSN nodes. This paper explores how to design efficient sensing and classification algorithms that achieve reliable sensing performance on energy-and-cost-effective hardware without special powerful nodes in a continuously changing physical environment. This paper present the detection and classification system in a cutting-edge surveillance sensor network, which classifies vehicles, persons, and persons carrying ferrous objects, and tracks these targets with a maximum error in velocity of 15%.
| Publisher | Association for Computing Machinery | File Format | |
|---|---|---|---|
| Date Published | November 2005 | ||
| Format | White Papers | ||
| Topics | |||
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