Spatial queries for extracting data from wireless sensor networks are important for many applications, such as environmental monitoring and military surveillance. One such query i...
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 algorithms for building and maintaining efficient collection trees that provide the conduit to disseminate data required for processing monitoring queries...
Wireless Sensor Network (WSN) technology is now mature enough to be used in numerous application domains. However, due to the restricted amount of energy usually allocated to each...
Motivated by the paradigm of event-based monitoring, which can potentially alleviate the inherent bandwidth and energy constraints associated with wireless sensor networks, we con...