Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/30234
DC FieldValueLanguage
dc.contributorDepartment of Computing-
dc.creatorWang, M-
dc.creatorCao, J-
dc.creatorChen, B-
dc.creatorXu, Y-
dc.creatorLi, J-
dc.date.accessioned2014-12-19T04:18:48Z-
dc.date.available2014-12-19T04:18:48Z-
dc.identifier.isbn9783540735489-
dc.identifier.issn0302-9743-
dc.identifier.urihttp://hdl.handle.net/10397/30234-
dc.description4th International Conference on Ubiquitous Intelligence and Computing: Building Smart Worlds in Real and Cyber Spaces, UIC 2007, Hong Kong, 11-13 July 2007en_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.subjectDistributed processingen_US
dc.subjectStructural health monitoringen_US
dc.subjectUbiquitous computingen_US
dc.subjectWireless sensor networken_US
dc.titleDistributed processing in wireless sensor networks for structural health monitoringen_US
dc.typeConference Paperen_US
dc.identifier.spage103-
dc.identifier.epage112-
dc.identifier.volume4611 LNCS-
dcterms.abstractWireless Sensor Networks (WSNs) have found many applications in a variety of ubiquitous computing environments. One of the key applications is Structural Health Monitoring (SHM) which seeks to monitor the functionality and detect the possible damages of large civil engineering structures, by measuring the structural responses to ambient or forced excitation. WSNs are a promising new technique for SHM, but the contradicting considerations on the unique characteristics of WSNs and the inherent requirements of SHM pose challenges for practical implementation. Distributed processing in WSNs can help reduce energy consumption, make efficient use of network bandwidth, and improve system response time. In this paper, we analyze the design issues of WSN-based SHM, and propose distributed processing architecture with algorithms. Results of performance the evaluations using both simulation and emulation demonstrate the effectiveness of our proposed approach.-
dcterms.bibliographicCitationLecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics), 2007, v. 4611 LNCS, p. 103-112-
dcterms.isPartOfLecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics)-
dcterms.issued2007-
dc.identifier.scopus2-s2.0-38049034060-
dc.identifier.eissn1611-3349-
dc.identifier.rosgroupidr38965-
dc.description.ros2007-2008 > Academic research: refereed > Refereed conference paper-
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