Full metadata record
DC Field | Value | Language |
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dc.citation.number | 6 | - |
dc.citation.startPage | 792 | - |
dc.citation.title | SENSORS | - |
dc.citation.volume | 16 | - |
dc.contributor.author | Kim, Robin E. | - |
dc.contributor.author | Mechitov, Kirill | - |
dc.contributor.author | Sim, Sung-Han | - |
dc.contributor.author | Spencer, Billie F. | - |
dc.contributor.author | Song, Junho | - |
dc.date.accessioned | 2023-12-21T23:40:21Z | - |
dc.date.available | 2023-12-21T23:40:21Z | - |
dc.date.created | 2016-06-14 | - |
dc.date.issued | 2016-06 | - |
dc.description.abstract | Structural health monitoring (SHM) using wireless smart sensors (WSS) has the potential to provide rich information on the state of a structure. However, because of their distributed nature, maintaining highly robust and reliable networks can be challenging. Assessing WSS network communication quality before and after finalizing a deployment is critical to achieve a successful WSS network for SHM purposes. Early studies on WSS network reliability mostly used temporal signal indicators, composed of a smaller number of packets, to assess the network reliability. However, because the WSS networks for SHM purpose often require high data throughput, i.e., a larger number of packets are delivered within the communication, such an approach is not sufficient. Instead, in this study, a model that can assess, probabilistically, the long-term performance of the network is proposed. The proposed model is based on readily-available measured data sets that represent communication quality during high-throughput data transfer. Then, an empirical limit-state function is determined, which is further used to estimate the probability of network communication failure. Monte Carlo simulation is adopted in this paper and applied to a small and a full-bridge wireless networks. By performing the proposed analysis in complex sensor networks, an optimized sensor topology can be achieved. | - |
dc.identifier.bibliographicCitation | SENSORS, v.16, no.6, pp.792 | - |
dc.identifier.doi | 10.3390/s16060792 | - |
dc.identifier.issn | 1424-8220 | - |
dc.identifier.scopusid | 2-s2.0-84971667728 | - |
dc.identifier.uri | https://scholarworks.unist.ac.kr/handle/201301/19676 | - |
dc.identifier.url | http://www.mdpi.com/1424-8220/16/6/792 | - |
dc.identifier.wosid | 000378756500040 | - |
dc.language | 영어 | - |
dc.publisher | MDPI AG | - |
dc.title | Probabilistic assessment of high-throughput wireless sensor networks | - |
dc.type | Article | - |
dc.description.isOpenAccess | TRUE | - |
dc.relation.journalWebOfScienceCategory | Chemistry, Analytical; Engineering, Electrical & Electronic; Instruments & Instrumentation | - |
dc.relation.journalResearchArea | Chemistry; Engineering; Instruments & Instrumentation | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordAuthor | High-throughput data transfer | - |
dc.subject.keywordAuthor | Network communication reliability | - |
dc.subject.keywordAuthor | Probabilistic assessment | - |
dc.subject.keywordAuthor | Structural health monitoring | - |
dc.subject.keywordAuthor | Wireless sensor networks | - |
dc.subject.keywordPlus | MODAL-ANALYSIS | - |
dc.subject.keywordPlus | BRIDGE | - |
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