The problem of false-positive RFID tag reads i.e., tags that have been read unintentionally by a reader, is crucial for the actual implementation of RFID solutions in the real world. Prior research has shown that the use of the low-level reader data is suitable to approach this problem and it is the scope of this paper to evaluate the use of alternative RFID reader antenna setups to support this idea. We collected a large number of data in a productive RFID enabled distribution center, derived additional knowledge from our findings and used it to train a machine learning algorithm for the detection of such false-positive reads. It will be shown that the proposed solutions significantly improve the previously in the literature presented classification algorithms.
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