Dr. Halgamuge is a Professor in the Melbourne School of Engineering of The University of Melbourne and a member of
the school wide initiative of Biomedical Engineering. He received Dipl.‐Ing (1990) and Dr.‐Ing (1995) degrees in
Electrical Engineering from Technical University of Darmstadt and B.Sc. Engineering degree from University of
Moratuwa (1984).
He leads a group of postdoctoral fellows and PhD students working on Pattern Recognition and Optimization.
Dr. Halgamuge is the co‐author of over 60 journal papers, 150 conference papers (h‐index 21), 8 books and 15
book chapters.
 

Propagation of a natural disaster across a landscape is stochastic in nature. However, the pattern may have an underlying structure in a given geographical primitive (alongside the river banks in the case of a flood, driven by the wind patterns in
the case of a forest fire, etc). We discuss about models that combines prior knowledge with in-coming stochastic data to
predict expected times of failure at various locations to optimally prepare sensor nodes to capture vital environmental
events with limited on-board power, a hopping mechanism to enable sensor nodes to be mobile to achieve maximum
resolution of sensing, and a new method of orphan node management enabling the sensor network to be robust in the
presence of random malfunctioning of sensor nodes. We will also present some of the recent sensor network deployments.

 

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