Efficient RFID Data Cleaning in Supply Chain Management

Hua FAN  Quanyuan WU  Jianfeng ZHANG  

IEICE TRANSACTIONS on Information and Systems   Vol.E96-D   No.7   pp.1557-1560
Publication Date: 2013/07/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.E96.D.1557
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Artificial Intelligence, Data Mining
data cleaning,  RFID technology,  Bayesian inference,  maximum entropy model,  supply chain management,  

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Despite the improvement of the accuracy of RFID readers, there are still erroneous readings such as missed reads and ghost reads. In this letter, we propose two effective models, a Bayesian inference-based decision model and a path-based detection model, to increase the accuracy of RFID data cleaning in RFID based supply chain management. In addition, the maximum entropy model is introduced for determining the value of sliding window size. Experiment results validate the performance of the proposed method and show that it is able to clean raw RFID data with a higher accuracy.