Measuring the Uncertainty of RFID Data Streams
نویسندگان
چکیده
RFID technology is widely used in the fields of location and position awareness. The RFID data streams are uncertain and need accurate and timely processing, since they are influenced by many factors. We propose an uncertain data optimal algorithm for RFID data streams. By analyzing the existing deficiency in the conventional particle filter method, we use a method based on entropy to derive the optimal weighting of features. We also use possible degree matrix to choose the best particle, capture the current state of the object effectively from uncertain RFID data streams. The optimization results of algorithms make sampling set move to the region that has a larger posteriori density value, so as to increase the calculation efficiency and significantly reduce the required number of particles for precise positioning. Finally, the experiments show that this method can effectively measure the uncertainty contained in the original RFID data streams.
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