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An optimization framework for solving RFID reader placement problem using greedy approach

Publication Type : Conference Paper

Publisher : 2017 4th International Conference on Advanced Computing and Communication Systems,

Source : 2017 4th International Conference on Advanced Computing and Communication Systems, ICACCS 2017, Institute of Electrical and Electronics Engineers Inc., Volume 2017-January, Manipal University, p.900-905 (2017)

Url : https://www.scopus.com/inward/record.uri?eid=2-s2.0-85038923868&doi=10.1109%2fICACCI.2017.8125956&partnerID=40&md5=c2e625e6ee38f98cc744300fa593c105

ISBN : 9781509045594

Keywords : Coverage, Electromagnetic fields, Greedy approaches, Radio frequency identification (RFID), ReaderPlacement, RFID readers, TAGs

Campus : Coimbatore

School : School of Engineering

Department : Computer Science

Year : 2017

Abstract : A RFID (Radio-Frequency Identification) system consists of RFID readers and tags.RFID technology uses electromagnetic fields to identify the location of the objects attached with the tag and track them continuously. The tags contain electronically stored information about the objects. The most essential requirement for setting up a RFIDenabled system is to deploy (locating and positioning) the RFID readers in order to ensure total coverage of all the RFID tags in an area. Finding an optimal number of readers required and their positions to cover all the tags is an important problem to be solved. Hence, this paper proposes a simple simulation strategy for finding optimal number of RFID readersand their positions for circular coverage using Greedy approach with 100% coverage of tags. The experimental set up and the results are explained in this paper.

Cite this Research Publication : N. Rubini, Prasanthi, C., Subanidha, S., Vamsi, T. N. S., and Dr. Jeyakumar G., “An optimization framework for solving RFID reader placement problem using greedy approach”, in 2017 4th International Conference on Advanced Computing and Communication Systems, ICACCS 2017, Manipal University, 2017, vol. 2017-January, pp. 900-905.

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