Escalation: Complex Event Detection in Wireless Sensor Networks

by Michael Zoumboulakis , George Roussos

Citations:

6 - 2 self

Datum	Value	Source
TITLE	Escalation: Complex Event Detection in Wireless Sensor Networks	SVM HeaderParse 0.2
AUTHOR NAME	Michael Zoumboulakis	SVM HeaderParse 0.2
AUTHOR AFFIL	School of Computer Science and Information Systems,; Birkbeck College, University of London	SVM HeaderParse 0.2
AUTHOR ADDR	Malet Street, London WC1E 7HX, UK	SVM HeaderParse 0.2
AUTHOR NAME	George Roussos	SVM HeaderParse 0.2
AUTHOR AFFIL	School of Computer Science and Information Systems,; Birkbeck College, University of London	SVM HeaderParse 0.2
AUTHOR ADDR	Malet Street, London WC1E 7HX, UK	SVM HeaderParse 0.2
ABSTRACT	Abstract. We present a new approach for the detection of complex events in Wireless Sensor Networks. Complex events are sets of data points that correspond to interesting or unusual patterns in the underlying phenomenon that the network monitors. Our approach is inspired from time-series data mining techniques and transforms a stream of realvalued sensor readings into a symbolic representation. Complex event detection is then performed using distance metrics, allowing us to detect events that are difficult or even impossible to describe using traditional declarative SQL-like languages and thresholds. We have tested our approach with four distinct data sets and the experimental results were encouraging in all cases. We have implemented our approach for the TinyOS and Contiki Operating Systems, for the Sky mote platform.	SVM HeaderParse 0.2
CITATIONS	30 found	ParsCit 1.0