CSMA Neighbors Identification in Body Sensor Networks
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Thiel, David V
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Abstract
A CSMA algorithm was implemented and tested using 2.45 GHz wearable sensors on five human subjects moving in formation. The algorithm forces the nodes to repeatedly sense the carrier frequency to recognize when other nodes are in/out of coverage. The paper reports different sink nodes location on the body and the effect of transmitter power on the reliability. The results showed 100% successful wireless communications between sink nodes within coverage. Allowing this information to be available in real time have a significant importance on measuring up athlete proximity and performance with respect to time spent on one or multiple locations.
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2
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6
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© 2018 by the authors; Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Nanotechnology
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Sabti, HA; Thiel, DV, CSMA Neighbors Identification in Body Sensor Networks, Proceedings, 2 (6), pp. 291:1-291:7