Adaptive cleaning for RFID data streamsAdaptive cleaning for RFID data streams Πλήρης Δημοσίευση σε Συνέδριο Conference Full Paper 2015-12-012006enTo compensate for the inherent unreliability of RFID data streams, most RFID middleware systems employ a “smoothing filter”, a sliding-window aggregate that interpolates for lost readings. In this paper, we propose SMURF, the first declarative, adaptive smoothing filter for RFID data cleaning. SMURF models the unreliability of RFID readings by viewing RFID streams as a statistical sample of tags in the physical world, and exploits techniques grounded in sampling theory to drive its cleaning processes. Through the use of tools such as binomial sampling and π-estimators, SMURF continuously adapts the smoothing window size in a principled manner to provide accurate RFID data to applications.http://creativecommons.org/licenses/by/4.0/163-174 32nd International Conference on Very Large Data BasesProceedings of the 32nd International Conference on Very Large Data Bases Shawn R. Jeffery Garofalakis Minos Γαροφαλακης Μινως Franklin Michael J. Association for Computing Machinery Databases technology