In recent years there has been an emergence of a number of new sensing concepts, many of which involve inexpensive and small sensors that can, in principle, be deployed in large numbers to provide enhanced spatio-temporal sensing coverage in ways that are either prohibitively expensive or impossible using conventional sensing assets. Realizing the potential of such large, distributed sensor systems, however, requires major advances in the theory and fundamental understanding of distributed data fusion in highly uncertain environments using sensing/communications nodes that are severely constrained in computation and communication capabilities. The overall goal of this MURI is to further this basic theory and understanding by addressing problems including: consistent fusion algorithms for networked sensors; adaptive collaborative processing in highly uncertain environments; and transmission of information in large and uncertain networks. Other major goals of this program are the training of graduate students and post-doctoral associates so that they are equipped to tackle multidisciplinary challenges such as those embedded in the SensorWeb concept and to communicate our ideas and results to others in the DoD community to further efforts aimed at realizing the potential of microsensor arrays.
This MURI is funded through the U.S. Army Research Office, Modeling of Complex Systems Program. The Research Topic Chief for this MURI is Dr. John Lavery (firstname.lastname@example.org). Our team involves researchers at 3 universities under the direction of Professors Sanjoy K. Mitter and Alan S. Willsky of M.I.T., Professor P.R. Kumar of the University of Illinois, and Professor Sanjeev Kulkarni of Princeton University. Other faculty and numerous students and post-doctoral associates at these universities are also involved with this program. We are also developing interactions with Army and other DoD Labs, federally funded research and development centers, and industrial partners.
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