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...
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 study the problem of localizing and tracking multiple moving targets in wireless sensor networks, from a network design perspective i.e. towards estimating the least possible n...
Underwater Acoustic Sensor Networks (UW-ASNs) consist of devices with sensing, processing, and communication capabilities that are deployed underwater to perform collaborative moni...
— This paper investigates implementation and design issues for a heterogeneous network for structural monitoring. The proposed application uses wireless sensors and the controlle...