针对制造业RFID不确定数据的分层处理模型

Hierarchical Processing Model for RFID Uncertain Data in Manufacturing

射频识别(RFID)技术的原始数据流本身含有大量不确定数据,无法被企业和用户直接使用。为此,对RFID不确定数据的产生和分类进行研究,得出这些不确定数据均由系统重读、多读和漏读所致的结论,并针对实际应用提出一种分层的处理模型,删除、纠正和填补这些不确定数据。实验结果表明,该分层处理模型能通过分层处理提高标签和对象的识别率,从而提升系统的可靠性。

Because the original data stream of Radio Frequency Identification（ RFID） technology itself contains a large number of uncertain data,it cannot be used directly by businesses and users. This paper discusses the generation and classification of RFID uncertain data,finds out that these uncertain data are caused by duplicated reading,repeated reading and missed reading,and proposes a hierarchical processing model for practical application to delete,correct and fill these uncertain data. Experimental results showthat the proposed model can improve the recognition rate of the label and the object through the hierarchical processing,and ultimately improve the reliability of the system.