Deriving Spatio-temporal Query Results in Sensor Networks

Abstract

Tracking moving objects in relation to regions of interest, e.g., for pollution control or habitat monitoring, is an important application of Sensor Networks (SN). Research on Moving Object Databases has resulted in sophisticated mechanisms for querying moving objects and regions declaratively. Applying these results to SN in a straightforward way is not possible: First, sensor nodes typically can only determine that an object is in their vicinity, but not the exact position. Second, nodes may fail, or areas may be unobservable. All this is problematic because the evaluation of spatio-temporal queries requires precise knowledge about object positions. In this paper we specify meaningful results of spatio-temporal queries, given those SN-specific phenomena, and say how to derive them from object detections by sensor nodes. We distinguish between objects which definitely fulfill the query and those that could possibly do so, but where those inaccuracies are in the way of a definite answer. We study both spatio-temporal predicates as well as spatio-temporal developments, i.e., sequences of predicates describing complex movement patterns of objects.