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...
Estimating the number of people in a crowded environment is a central task in civilian surveillance. Most vision-based counting techniques depend on detecting individuals in order...
In recent years, wireless sensor networking has shown great promise in applications ranging from industrial control, environmental monitoring and inventory tracking. Given the res...
Anthony Rowe, Karthik Lakshmanan, Ragunathan Rajku...
The recent Federal Communications Commission regulations for ultra-wideband (UWB) transmission systems have sparked a surge of research interests in the UWB technology. One of the ...
Many applications in wireless sensor networks rely on data from neighboring nodes. However, the effort for developing efficient solutions for sharing data in the neighborhood is of...
Andreas Lachenmann, Daniel Minder, Kurt Rothermel,...