Please use this identifier to cite or link to this item: http://dspace.unimap.edu.my:80/xmlui/handle/123456789/26539
Title: Comparative performance analysis of wireless RSSI in wireless sensor networks motes in tropical mixed-crop precision farm
Authors: Azizi, Harun
Ramli, M. F.
Latifah Munirah, Kamarudin
Ndzi, David Lorater
Ali Yeon, Md Shakaff, Prof. Dr.
Ammar, Zakaria
Mahmad, Nor Jaafar
zz_harun@yahoo.com
a_chuck768@yahoo.com
latifahmunirah @ unimap.edu.my
Keywords: Mixed-crop
Received signal strength
RSSI
Wireless sensor network (WSN)
Issue Date: 8-Feb-2012
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Citation: p. 606-610
Series/Report no.: Proceedings of the 3rd International Conference on Intelligent Systems Modelling and Simulation 2012
Abstract: T o provide reliable and adequate network coverage whilst minimizing the cost of wireless sensor network ( WSN ) deployments , detailed knowledge of wireless signal propagation within the specific environment s is required . There are many WSN devices on the marke t that have been developed using proprietary systems and therefore have different performances , although implementing similar standards . This paper presents a comparative performance measurement and analysis of three types of WSN devices evaluated for appl ication in a mixed - crop farm. The results show that the Xbee - PRO maintains very strong RSSI values in open field measurements that are sometime 15 dBm higher than those obtained from the IRIS and Microchip motes. Overall, two important factors that influen ce WSN node performances are antenna height and the type of antenna used. Whip omni - directional antenna has been s hown to double the range of the WSN node compared to a patch antenna. R esult s also show that the l og - distance propagation model is a more flex ible model that can be used to model a variety of channels, although it lacks standard global parameter values .
Description: Link to publisher's homepage at http://ieeexplore.ieee.org
URI: http://dspace.unimap.edu.my/123456789/26539
ISBN: 978-076954668-1
ISSN: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6169771
Appears in Collections:Conference Papers
Ali Yeon Md Shakaff, Dato' Prof. Dr.
Ammar Zakaria, Associate Professor Dr.



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