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...
This paper presents the Real-Time Event Detection Service using Data Service Middleware (DSWare). DSWare provides data-centric and group-based services for sensor networks. The rea...
— Sensor networks (SNETs) for monitoring spatial phenomena has emerged as an area of significant practical interest. We focus on the important problem of detection of distribute...
— Faults in WSN are very common and appear in different levels of the system. For pervasive applications to be adopted by end-users there is a need for autonomic selfhealing. Thi...
Distributed sensor networks are highly prone to accidental errors and malicious activities, owing to their limited resources and tight interaction with the environment. Yet only a...
Claudio Basile, Meeta Gupta, Zbigniew Kalbarczyk, ...