CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Anomaly Detection and Elimination Algorithm for RFID Data in Healthcare

by A. Anny Leema, Hemalatha.m
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 49 - Number 3
Year of Publication: 2012
Authors: A. Anny Leema, Hemalatha.m
10.5120/7606-0619

A. Anny Leema, Hemalatha.m . Anomaly Detection and Elimination Algorithm for RFID Data in Healthcare. International Journal of Computer Applications. 49, 3 ( July 2012), 11-18. DOI=10.5120/7606-0619

@article{ 10.5120/7606-0619,
author = { A. Anny Leema, Hemalatha.m },
title = { Anomaly Detection and Elimination Algorithm for RFID Data in Healthcare },
journal = { International Journal of Computer Applications },
issue_date = { July 2012 },
volume = { 49 },
number = { 3 },
month = { July },
year = { 2012 },
issn = { 0975-8887 },
pages = { 11-18 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume49/number3/7606-0619/ },
doi = { 10.5120/7606-0619 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:45:19.628758+05:30
%A A. Anny Leema
%A Hemalatha.m
%T Anomaly Detection and Elimination Algorithm for RFID Data in Healthcare
%J International Journal of Computer Applications
%@ 0975-8887
%V 49
%N 3
%P 11-18
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The RFID technology has penetrated into all the sectors like supply chain automation, asset tracking, medical/Health Care applications, people tracking, Manufacturing, Retail, Warehouses, Livestock Timing and the healthcare sector due to its increased functionality, low cost, high reliability and easy-to-use capabilities. RFID system produces data that are unreliable, low-level, and rarely able to be used directly by applications. This paper discusses the existing physical, middleware and deferred approaches to deal with anomalies. Each approach has its own drawbacks. To clean the anomaly - false positive in an effective manner we have chosen the integrated approach of middleware and deferred. The premise taken is based on cellular for detecting out of the range readings . The RFID readers have Omni-directional antenna and hence there are possibilities for the adjacent regions to over lap with each other. Algorithm proposed in this paper do not deal with any physical device , but rather integrate middleware and deferred to construct RFID hybrid system that lighten issues associated with using RFID data through adaptive cleaning technique. The resultant data is cleaned data and it can be used for any high end applications. Simulation shows our approach deals with RFID data more efficiently and accurately.

References
  1. P. F. Drucker, "The essential Drucker: selections from the management works of Peter F. Drucker",New York: HarperBusiness, 2001.
  2. Chunkai Zhang , Yan Chen "Application oriented Data Cleaning for RFID middleware", IEEE, 2011.
  3. U. S. Government Accountability Office, "Radio Frequency Identification Technology in the Federal Government", 441 G Street NW, Room LM Washington, D. C. 20548, 2005.
  4. . Sudarshan S. Chawathe, Venkat Krishnamurthy, Sridhar Ramachandran, and Sanjay Sarma, "Managing RFID Data", In Proceedings of the 30th VLDB Conference, pp. 1189-1195, 2004
  5. C. Floerkemeier and M. Lampe. Issues with RFID Usage in Ubiquitous Computing Applications. In Pervasive, pages 188–193, 2004.
  6. S. R. Jeffery, G. Alonso, M. J. Franklin, W. Hong, and J. Widom. Declarative Support for Sensor Data Cleaning. In Pervasive, pages 83–100, 2006
  7. S. R. Jeffery, M. N. Garofalakis, and M. J. Franklin. Adaptive Cleaning for RFID Data Streams. In VLDB, pages 163–174, 2006.
  8. J. Rao, S. Doraiswamy, H. Thakkar and L. S. Colby, A Deferred Cleansing Method for RFID Data Analytics, in Proceedings of the 32nd VLDB Conference, pp. 175-186, 2006.
  9. . Angela M. Wicks, John K. Visich and Suhong Li, "Radio Frequency Identification Applications in Hospital Environments", , Vol. 84, No. 3, pp. 3-9, 2006.
  10. A. Anny Leema, M. Hemalatha , "Optimizing Operational Efficiency and Enhancing Data Reliability using Effective and Adaptive CleaningApproach for RFID in Healthcare ",International Journal of Computer Applications (IJCA)
  11. A. Lahtela, "A Short Overview of the RFID Technology in Healthcare", Systems and Networks Communications,2009, ICSNC '09, In Proceedings of Fourth International Conference on, pp. 165-169, 2009 Cleansing Method for RFID Data Analytics. In VLDB, pages 175–186,2006.
  12. A. Anny Leema, M. Hemalatha , "An effective and adaptive data cleaning technique for colossal RFID data sets in healthcare"in WSEAS TRANSACTIONS on INFORMATION SCIENCE and APPLICATIONS, pages 243-252, ISSN: 1790-0832, Issue 6, Volume 8, 2011.
  13. Bettina Fazzinga, Sergio Flesca, Elio Masciari and Filippo Furfaro, "Efficient and effective RFID data warehousing", In proceedings of the 2009 International Database Engineering & Applications Symposium,pp. 251-258 , 2009.
Index Terms

Computer Science
Information Sciences

Keywords

RFID technology RFID data characteristics Existing approach proposed approach case study

Powered by PhDFocusTM