文章基本信息

标题：An Improved Algorithm for Reducing False and Duplicate Readings in RFID Data Stream Based on an Adaptive Data Cleaning Scheme
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作者：Neha Dhama ; Meghna Sharma
期刊名称：International Journal of Computer Trends and Technology
电子版ISSN：2231-2803
出版年度：2013
卷号：4
期号：4-5
出版社：Seventh Sense Research Group
摘要：RFID technology is increasing rapidly and being successfully applied to various sectors such as supply chain management, manufacturing, Retail, warehouses, wallmart and health care applications. The data stream produced by RFID system is sometimes unreliable, inaccurate, low level. As a result, there is a heavy load of unreliable data which is useless for higher level application. Therefore, RFID data cleaning is the most important task for the successful deployment of RFID systems. Unreliable data appears in three forms of reading errors false positive (unexpected), false negative (missed) and duplicate readings. Most common technique which is used by RFID middleware is the use of sliding window filters. In this paper, based on the individual tag reading environment, false readings and duplicate reading errors are reduced by a new adaptive data cleaning window scheme called WSTD. This technique is used along with some of the concepts of SMURF but with an improved transition detection mechanism as SMURF has some drawbacks. The result has been evaluated on RFID database. Also, comparison has been done with the existing approach i.e. SMURF. Simulation shows our approach deals with RFID data more accurately.
关键词：data; rfid; international; cleaning; computer; journal; false