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dc.contributor.authorDyo, Vladimiren_GB
dc.contributor.authorYousef, Kharsimen_GB
dc.contributor.authorEllwood, Stephen A.en_GB
dc.contributor.authorMacdonald, David W.en_GB
dc.contributor.authorMarkham, Andrewen_GB
dc.contributor.authorTrigoni, Nikien_GB
dc.contributor.authorWohlers, Ricklefen_GB
dc.contributor.authorMascolo, Ceciliaen_GB
dc.contributor.authorPásztor, Benceen_GB
dc.contributor.authorScellato, Salvatoreen_GB
dc.date.accessioned2012-11-05T09:59:39Zen
dc.date.available2012-11-05T09:59:39Zen
dc.date.issued2012-09en
dc.identifier.citationDyo, V. et al (2012) 'WILDSENSING' ACM Transactions on Sensor Networks 8 (4):1 (article No. 29)en_GB
dc.identifier.issn1550-4859en
dc.identifier.doi10.1145/2240116.2240118en
dc.identifier.urihttp://hdl.handle.net/10547/250915en
dc.description.abstractThe increasing adoption of wireless sensor network technology in a variety of applications, from agricultural to volcanic monitoring, has demonstrated their ability to gather data with unprecedented sensing capabilities and deliver it to a remote user. However, a key issue remains how to maintain these sensor network deployments over increasingly prolonged deployments. In this article, we present the challenges that were faced in maintaining continual operation of an automated wildlife monitoring system over a one-year period. This system analyzed the social colocation patterns of European badgers (Meles meles) residing in a dense woodland environment using a hybrid RFID-WSN approach. We describe the stages of the evolutionary development, from implementation, deployment, and testing, to various iterations of software optimization, followed by hardware enhancements, which in turn triggered the need for further software optimization. We highlight the main lessons learned: the need to factor in the maintenance costs while designing the system; to consider carefully software and hardware interactions; the importance of rapid prototyping for initial deployment (this was key to our success); and the need for continuous interaction with domain scientists which allows for unexpected optimizations.
dc.language.isoenen
dc.publisherAssociation for Computing Machinery (ACM)en_GB
dc.relation.urlhttp://dl.acm.org/citation.cfm?doid=2240116.2240118en_GB
dc.titleWILDSENSING: design and deployment of a sustainable sensor network for wildlife monitoringen
dc.typeArticleen
dc.identifier.journalACM Transactions on Sensor Networksen_GB
html.description.abstractThe increasing adoption of wireless sensor network technology in a variety of applications, from agricultural to volcanic monitoring, has demonstrated their ability to gather data with unprecedented sensing capabilities and deliver it to a remote user. However, a key issue remains how to maintain these sensor network deployments over increasingly prolonged deployments. In this article, we present the challenges that were faced in maintaining continual operation of an automated wildlife monitoring system over a one-year period. This system analyzed the social colocation patterns of European badgers (Meles meles) residing in a dense woodland environment using a hybrid RFID-WSN approach. We describe the stages of the evolutionary development, from implementation, deployment, and testing, to various iterations of software optimization, followed by hardware enhancements, which in turn triggered the need for further software optimization. We highlight the main lessons learned: the need to factor in the maintenance costs while designing the system; to consider carefully software and hardware interactions; the importance of rapid prototyping for initial deployment (this was key to our success); and the need for continuous interaction with domain scientists which allows for unexpected optimizations.


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  • Centre for Wireless Research (CWR)
    The Centre for Wireless Research brings together expertise in the areas of mobile and wireless sensor networks. The breadth and depth of the expertise make the Centre rich with research and innovation potential.

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