X-CleLo: intelligent deterministic RFID data and event transformer

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Author(s)
Darcy, Peter
Stantic, Bela
Sattar, Abdul
Year published
2012
Metadata
Show full item recordAbstract
Recently, passive Radio Frequency Identification (RFID) systems have received an increased amount of attention as researchers have worked to implement a stable and reliable system. Unfortunately, despite vast improvements in the quality of RFID technology, a significant amount of erroneous data is still captured in the system. Currently, the problems associated with RFID have been addressed by cleaning algorithms to enhance the data quality. In this paper, we present X-CleLo, a means to intelligently clean and transform the dirty data into highlevel events using Clausal Defeasible Logic. The extensive experimental study we ...
View more >Recently, passive Radio Frequency Identification (RFID) systems have received an increased amount of attention as researchers have worked to implement a stable and reliable system. Unfortunately, despite vast improvements in the quality of RFID technology, a significant amount of erroneous data is still captured in the system. Currently, the problems associated with RFID have been addressed by cleaning algorithms to enhance the data quality. In this paper, we present X-CleLo, a means to intelligently clean and transform the dirty data into highlevel events using Clausal Defeasible Logic. The extensive experimental study we have conducted has shown that the X-CleLo method has several advantages over currently utilised cleaning techniques and achieves a higher cleaning and event discovery rate.
View less >
View more >Recently, passive Radio Frequency Identification (RFID) systems have received an increased amount of attention as researchers have worked to implement a stable and reliable system. Unfortunately, despite vast improvements in the quality of RFID technology, a significant amount of erroneous data is still captured in the system. Currently, the problems associated with RFID have been addressed by cleaning algorithms to enhance the data quality. In this paper, we present X-CleLo, a means to intelligently clean and transform the dirty data into highlevel events using Clausal Defeasible Logic. The extensive experimental study we have conducted has shown that the X-CleLo method has several advantages over currently utilised cleaning techniques and achieves a higher cleaning and event discovery rate.
View less >
Journal Title
Personal and Ubiquitous Computing
Volume
16
Issue
3
Copyright Statement
© 2011 Springer London. This is an electronic version of an article published in Personal and Ubiquitous Computing, March 2012, Volume 16, Issue 3, pp 259-269. Personal and Ubiquitous Computing is available online at: http://www.springerlink.com/ with the open URL of your article.
Subject
Artificial intelligence not elsewhere classified
Data engineering and data science
Distributed computing and systems software
Information systems
Design
Information and computing sciences