—Urban sensing where mobile users continuously gather, process, and share location-sensitive sensor data (e.g., street images, road condition, traffic flow) is emerging as a ne...
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...
We use the theory and algorithms developed for so-called shiftinvariant spaces to develop a novel distributed architecture for sampling and reconstructing non-bandlimited fields i...
—One of the most common and important applications of wireless sensor networks is target tracking. We study it in its most basic form, assuming the binary sensing model in which ...
In wireless sensor networks, multi-hop localization schemes are very vulnerable to various attacks such as wormholes and range modification attacks. In this paper, we propose a rob...