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In this paper, the authors 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, they 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. They further consider challenges in instantiating such a system in large distributed settings and design techniques for distributed inference and query processing. The experimental results, using both real-world data and large synthetic traces, demonstrate the accuracy, efficiency, and scalability of the proposed techniques.
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