In this paper, we consider the following scenario: a set of mobile objects continuously track their positions in a road network and are able to communicate with a central server. ...
In this paper3 , we use Bayesian Networks as a means for unsupervised learning and anomaly (event) detection in gas monitoring sensor networks for underground coal mines. We show t...
X. Rosalind Wang, Joseph T. Lizier, Oliver Obst, M...
This paper presents a set of algorithms for efficiently evaluating join queries over static data tables in sensor networks. We describe and evaluate three algorithms that take adv...
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...
We propose a Polynomial-based scheme that addresses the problem of Event Region Detection (PERD) for wireless sensor networks (WSNs). Nodes of an aggregation tree perform function ...
Torsha Banerjee, Demin Wang, Bin Xie, Dharma P. Ag...