Offline cleaning of RFID trajectory data

Abstract

An offline cleaning technique is proposed for translating the readings generated by RFID-tracked moving objects into positions over a map. It consists in a grid-based two-way filtering scheme embedding a sampling strategy for addressing missing detections. The readings are first processed in time order: at each time point t, the positions (i.e., cells of a grid assumed over the map) compatible with the reading at t are filtered according to their reachability from the positions that survived the filtering for the previous time point. Then, the positions that survived the first filtering are re-filtered, applying the same scheme in inverse order. As the two phases proceed, a probability is progressively evaluated for each candidate position at each time point t: at the end, this probability assembles the three probabilities of being the actual position given the past and future positions, and given the reading at t. A sampling procedure is employed at certain steps of the first filtering phase to intelligently reduce the number of cells to be considered as candidate positions at the next steps, as their number can grow dramatically in the presence of consecutive missing detections. The proposed approach is experimentally validated and shown to be efficient and effective in accomplishing its task.