RFID Data Cleaning Based on Adaptive Window

摘要

Data captured by RFID reader often has errors including false negatives, false positives, and duplicates. In order to provide reliable data to RFID application, it is necessary to clean the collected data. SMURF (Statistical Smoothing for Unreliable RFID data) is a recently proposed data cleaning method based on adaptive window. However it does not work well when tag moves rapidly. To solve the problem, we propose an improved algorithm based on adaptive window. Factors, such as reader communication range, reading frequency, velocity of tag movement, affect the data cleaning result. Our new algorithm considers these factors dynamically in determination of the size of slide window. A new method is also proposed to fill data. Simulation shows our approach deals with RFID data more efficiently and accurately.