The Science Seminar Series: January 24, 2013
RFID Tag Could Mean the End of Bar Codes?
-----A Novel Bayesian Inference-Based Framework for RFID Data Cleansing
Dr. Haiquan (Victor) Chen
Department of Mathematics and Computer Science
Valdosta State University
Time: 4:00 -5:00pm
The past few years have witnessed the emergence of an increasing number of applications for tracking and tracing based on Radio Frequency Identification (RFID) technologies. However, raw RFID readings are usually of low quality and may contain numerous anomalies. An ideal solution for RFID data cleansing should address the following issues. First, in many applications, duplicate readings of the same object are very common. The solution should take advantage of the resulting data redundancy for data cleaning. Second, prior knowledge about the environment may help improve data quality, and a desired solution must be able to take into account such knowledge. Third, the solution should take advantage of physical constraints in target applications in order to elevate the accuracy of data cleansing. There are several existing RFID data cleansing techniques. However, none of them support all the aforementioned features. This talk focuses on a novel Bayesian inference-based framework for cleaning RFID raw data.