Interpreting RFID tracking data for simultaneously moving objects: An offline sampling-based approach

We consider the scenario of multiple RFID-tagged objects that simultaneously move across an indoor space where several RFID antennas are placed. We assume that a logical partition of the indoor space into a set of locations is given, along with a set of hard and weak integrity constraints describing both the valid movements of the objects and the capacity of the locations. In this setting, we address the problem of matching the collected readings to the trajectories(namely, the sequences of locations) followed by the target objects. We model this problem as estimating a probability distribution function over the possible matchings of the readings to the locations. The core of our approach is a novel Metropolis Hastings sampler that is guided by the integrity constraints to distinguish between likely and unlikely ways of interpreting the readings. The challenges of integrating the constraints into the sampler are discussed, and a thorough experimental analysis, where the proposed approach is compared with the state of the art, is provided.