EveTrack: An event localization and tracking scheme for WSNs in dynamic environments

This paper introduces EveTrack, an online and distributed method for localization and tracking of global and composite events. Based on hyper-ellipsoid clustering model, we compute the percentage contributions of the individual attributes in multi-attribute and correlated events. In addition, EveTrack utilizes spatio-temporal correlations between multiple events during its event identification phase. Finally, EveTrack estimates the event location using an iterative Linear Least Square (LLS) approach based on the event intensities estimated at different nodes. The results of our localization algorithm show 4-10 fold improvement in localization accuracy with significantly less computational complexity when compared to previously proposed event localization algorithms.

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