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.