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...
The large-scale deployment of wireless sensor networks (WSNs) and the need for data aggregation necessitate efficient organization of the network topology for the purpose of balan...
Wireless sensor networks are often studied with the goal of removing information from the network as efficiently as possible. However, when the application also includes an actuato...
Understanding the dynamics of bodies of water and their impact on the global environment requires sensing information over the full volume of water. We develop a gradientbased dec...
Carrick Detweiler, Marek Doniec, Mingshun Jiang, M...
Geographic routing is of interest for sensor networks because a point-to-point primitive is an important building block for data-centric applications. While there is a significant...
Jiangwei Zhou, Yu Chen, Ben Leong, Pratibha Sundar...