IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Understanding RFID (Radio Frequency Identification)

Understanding RFID (Radio Frequency Identification)
View Sample PDF
Author(s): Susan A. Vowels (Washington College, USA)
Copyright: 2010
Pages: 11
Source title: Ubiquitous and Pervasive Computing: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Judith Symonds (AUT University, New Zealand)
DOI: 10.4018/978-1-60566-960-1.ch006

Purchase

View Understanding RFID (Radio Frequency Identification) on the publisher's website for pricing and purchasing information.

Abstract

RFID, also known as radio frequency identification, is a form of Auto ID (automatic identification). Auto ID is defined as “the identification of an object with minimal human interaction” (Puckett, 1998). Auto ID has been in existence for some time; in fact, the bar code, the most ubiquitous form of Auto ID, celebrated its 30th year in commercial use in 2004 (Albright, 2004). Barcodes identify items through the encoding of data in various sized bars using a variety of symbologies, or coding methodologies. The most familiar type of barcode is the UPC, or universal product code, which provides manufacturer and product identification. While barcodes have proven to be very useful, and indeed, have become an accepted part of product usage and identity, there are limitations with the technology. Barcode scanners must have line of sight in order to read barcode labels. Label information can be easily compromised by dirt, dust, or rips. Barcodes take up a considerable footprint on product labels. Even the newer barcode symbologies, such as 2D, or two-dimensional, which can store a significant amount of data in a very small space (“Two dimensional…,” 2005) remain problematic. RFID proponents argue that limitations of barcodes are overcome through the use of RFID labeling to identify objects.

Related Content

Bin Guo, Yunji Liang, Zhu Wang, Zhiwen Yu, Daqing Zhang, Xingshe Zhou. © 2014. 20 pages.
Yunji Liang, Xingshe Zhou, Bin Guo, Zhiwen Yu. © 2014. 31 pages.
Igor Bisio, Alessandro Delfino, Fabio Lavagetto, Mario Marchese. © 2014. 33 pages.
Kobkaew Opasjumruskit, Jesús Expósito, Birgitta König-Ries, Andreas Nauerz, Martin Welsch. © 2014. 22 pages.
Viktoriya Degeler, Alexander Lazovik. © 2014. 23 pages.
Vlasios Kasapakis, Damianos Gavalas. © 2014. 26 pages.
Zhu Wang, Xingshe Zhou, Daqing Zhang, Bin Guo, Zhiwen Yu. © 2014. 18 pages.
Body Bottom