Evidence Filtering

Wireless sensor networks attempt to revolutionize
the way we interact with the physical world by
networking multitudes of small sensors attached to
wireless radios. This book presents a novel method
named Evidence Filtering for processing multi-
modality sensor data in such networks. Based on
Dempster-Shafer evidence theory, it allows one to
directly process temporally and spatially
distributed multi-modality sensor data and infer on
the `frequency' characteristics of events of
interest. Second part of the book covers distributed
methods to implement spatio-temporal filtering
applications in grid sensor networks. Based on the
Fornasini-Marchesini local state space model, these
distributed methods enable local actuation in
response to local events. The techniques discussed
here provide a highly effective toolset for one to
implement spatio-temporal filtering applications in
multi-modality grid sensor networks. This book also
covers past research in related areas and is
intended for students, engineers, scientists, and
researchers in the related disciplines.