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...
Habitat monitoring is an important driving application for wireless sensor networks (WSNs). Although researchers anticipate some challenges arising in the real-world deployments of...
Robert Szewczyk, Joseph Polastre, Alan M. Mainwari...
—Underwater Sensor Networks are typically distributed in nature and the nodes communicate using acoustic waves over a wireless medium. Such networks are characterized by long and...
Environment monitoring in coal mines is an important application of wireless sensor networks (WSNs) that has commercial potential. We discuss the design of a Structure-Aware Self-...
We propose a distributed on-demand power-management protocol for collecting data in sensor networks. The protocol aims to reduce power consumption while supporting fluctuating dem...