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...
—In this paper we present a new approach called cue-based networking that uses hints or cues about the physical environment to optimize networked application behavior. We define...
— We present Telos, an ultra low power wireless sensor module (“mote”) for research and experimentation. Telos is the latest in a line of motes developed by UC Berkeley to en...
The recent advances in miniaturization and the creation of low-power circuits, combined with small-sized batteries have made the development of wireless sensor networks a working ...
Wireless sensor networks have attracted attention from a diverse set of researchers, due to the unique combination of distributed, resource and data processing constraints. Howeve...