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An Active Low Cost Mesh Networking Indoor Tracking System

An Active Low Cost Mesh Networking Indoor Tracking System

Sean Carlin, Kevin Curran
Copyright: © 2014 |Volume: 6 |Issue: 1 |Pages: 35
ISSN: 1941-6237|EISSN: 1941-6245|EISBN13: 9781466652354|DOI: 10.4018/ijaci.2014010104
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MLA

Carlin, Sean, and Kevin Curran. "An Active Low Cost Mesh Networking Indoor Tracking System." IJACI vol.6, no.1 2014: pp.45-79. http://doi.org/10.4018/ijaci.2014010104

APA

Carlin, S. & Curran, K. (2014). An Active Low Cost Mesh Networking Indoor Tracking System. International Journal of Ambient Computing and Intelligence (IJACI), 6(1), 45-79. http://doi.org/10.4018/ijaci.2014010104

Chicago

Carlin, Sean, and Kevin Curran. "An Active Low Cost Mesh Networking Indoor Tracking System," International Journal of Ambient Computing and Intelligence (IJACI) 6, no.1: 45-79. http://doi.org/10.4018/ijaci.2014010104

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Abstract

Indoor radio frequency tracking systems are generally quite expensive and can vary in accuracy due to interference, equipment quality or other environmental factors. Due to these limiting factors of the technology, many businesses today find it hard to justify investing in RFID tracking technologies to improve the safety, efficiency and security of their working environments. The aim of this project was to provide a budget RFID tracking system that was capable of tracking a person or object through an indoor environment. To minimize the cost of the RFID tracking system, the components of the system were built from existing electronic equipment and hardware. The software was also written to minimize licensing and support fees allowing a cost effective budget RFID tracking system to be developed. The tracking system consists of a tag, reader nodes and a PC reader which utilize synapse RF 100 engines with python scripts embedded on to the chips. The tracking system software operates through a web portal utilizing web technologies such as HTML, JavaScript and PHP to allow the tags location to be represented on a two dimensional map using scalable vector graphics. During development of the system a new trilateration algorithm was developed and used convert the signals received from the tag to a virtual position on the map correlating to the actual physical position of the tag. A unique contribution of this system is the low cost of building which we estimate as less than £200 UK sterling for a five node system.

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