Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/4553
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dc.contributor.authorOnoufriou, Toulaen
dc.contributor.authorSoman, Rohan N.en
dc.contributor.authorChrysostomou, Christis-
dc.contributor.authorVotsis, Renos-
dc.contributor.authorKyriakides, Marios-
dc.contributor.otherΟνουφρίου, Τούλα-
dc.contributor.otherΧρυσοστόμου, Κρίστης-
dc.contributor.otherΒότσης, Ρένος-
dc.contributor.otherΚυριακίδης, Μάριος-
dc.date.accessioned2013-02-20T13:44:26Zen
dc.date.accessioned2013-05-17T10:36:30Z-
dc.date.accessioned2015-12-09T13:59:25Z-
dc.date.available2013-02-20T13:44:26Zen
dc.date.available2013-05-17T10:36:30Z-
dc.date.available2015-12-09T13:59:25Z-
dc.date.issued2012en
dc.identifier.citationBridge Maintenance, Safety, Management, Resilience and Sustainability:6th International Conference on Bridge Maintenance, Safety and Management, 2012, Stresa, Lake Maggioreen
dc.identifier.urihttps://hdl.handle.net/20.500.14279/4553-
dc.description.abstractStructural Health Monitoring (SHM) techniques have undergone a paradigm shift due to new emerging technologies and developments in the field of remote communications. The use of Wireless Sensor Networks (WSN) has been on an increase in the last decade due to its low cost deployment, ease of maintenance and increased efficiency. However, the battery life of the sensors of such networks is limited and hence puts severe restrictions on the use of this technology. Thus there is a need to enhance the life time of the network through optimizing the energy usage of sensors. Sensor placement for achieving network longevity might lead to loss of vital information, thus making the sensor placement ineffective from the SHM perspective. This paper focuses on optimizing the location of the sensors to cater to the specific requirements of structural engineering while adhering to the energy limitations imposed due to the use of WSN. In this paper a minimization problem is formulated first to optimize the number of sensors, and then Genetic Algorithm (GA) is used to optimize the sensor location for detecting structural vibration responses for SHM. The GA employs a fitness function that combines the determinant of Fisher Information Matrix (FIM) - an indicator of the information quality and the maximum energy used by the sensor node. The approach has been verified on an FE model of a long span bridge and compared with other optimal sensor placement principles in order to ascertain its suitability and effectiveness.en
dc.formatpdfen
dc.language.isoenen
dc.rights© 2012 Taylor & Francis Group.en
dc.subjectWireless sensor networksen
dc.subjectOptimization and computation seriesen
dc.subjectEmerging technologiesen
dc.titleOptimization of Wireless Sensor locations for SHM based on application demands and networking limitationsen
dc.typeConference Papersen
dc.collaborationCyprus University of Technology-
dc.subject.categoryCivil Engineering-
dc.countryCyprus-
dc.subject.fieldEngineering and Technology-
dc.dept.handle123456789/148en
item.languageiso639-1en-
item.cerifentitytypePublications-
item.openairetypeconferenceObject-
item.openairecristypehttp://purl.org/coar/resource_type/c_c94f-
item.fulltextNo Fulltext-
item.grantfulltextnone-
crisitem.author.deptDepartment of Civil Engineering and Geomatics-
crisitem.author.deptDepartment of Civil Engineering and Geomatics-
crisitem.author.deptDepartment of Civil Engineering and Geomatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0002-3361-1567-
crisitem.author.orcid0000-0002-7141-7423-
crisitem.author.orcid0000-0002-4433-2184-
crisitem.author.parentorgFaculty of Engineering and Technology-
crisitem.author.parentorgFaculty of Engineering and Technology-
crisitem.author.parentorgFaculty of Engineering and Technology-
Appears in Collections:Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation
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