  In this paper, we present the design of a scalable, distributed stream
processing system for RFID tracking and monitoring. Since RFID data lacks
containment and location information that is key to query processing, we
propose to combine location and containment inference with stream query
processing in a single architecture, with inference as an enabling mechanism
for high-level query processing. We further consider challenges in
instantiating such a system in large distributed settings and design techniques
for distributed inference and query processing. Our experimental results, using
both real-world data and large synthetic traces, demonstrate the accuracy,
efficiency, and scalability of our proposed techniques.
