Cost-conscious cleaning of massive RFID data sets

Hector Gonzalez, Jiawei Han, Xuehua Shen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Efficient and accurate data cleaning is an essential task for the successful deployment of RFID systems. Although important advances have been made in tag detection rates, it is still common to see a large number of lost readings due to radio frequency (RF) interference and tag-reader configurations. Existing cleaning techniques have focused on the development of accurate methods that work well under a wide set of conditions, but have disregarded the very high cost of cleaning in a real application that may have thousands of readers and millions of tags. In this paper, we propose a cleaning framework that takes an RFID data set and a collection of cleaning methods, with associated costs, and induces a cleaning plan that optimizes the overall accuracy-adjusted cleaning costs by determining the conditions under which inexpensive methods are appropriate, and those under which more expensive methods are absolutely necessary.

Original languageEnglish (US)
Title of host publication23rd International Conference on Data Engineering, ICDE 2007
Pages1268-1272
Number of pages5
DOIs
StatePublished - 2007
Event23rd International Conference on Data Engineering, ICDE 2007 - Istanbul, Turkey
Duration: Apr 15 2007Apr 20 2007

Publication series

NameProceedings - International Conference on Data Engineering
ISSN (Print)1084-4627

Other

Other23rd International Conference on Data Engineering, ICDE 2007
Country/TerritoryTurkey
CityIstanbul
Period4/15/074/20/07

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Information Systems

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