Geographical area network-structural health monitoring utility computing model

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dc.contributor.authorTariq, Hasan
dc.contributor.authorTahir, Anas
dc.contributor.authorTouati, Farid
dc.contributor.authorAl-Hitmi, Mohammed Abdulla E.
dc.contributor.authorCrescini, Damiano
dc.contributor.authorMnaouer, Adel Ben
dc.date.accessioned2020-01-23T11:57:20Z
dc.date.available2020-01-23T11:57:20Z
dc.date.copyright2019en_US
dc.date.issued2019
dc.descriptionThis article is not available at CUD collection. The version of scholarly record of this article is published in ISPRS International Journal of Geo-Information (2019), available online at: https://doi.org/10.3390/ijgi803015en_US
dc.description.abstractIn view of intensified disasters and fatalities caused by natural phenomena and geographical expansion, there is a pressing need for a more effective environment logging for a better management and urban planning. This paper proposes a novel utility computing model (UCM) for structural health monitoring (SHM) that would enable dynamic planning of monitoring systems in an efficient and cost-effective manner in form of a SHM geo-informatics system. The proposed UCM consists of networked SHM systems that send geometrical SHM variables to SHM-UCM gateways. Every gateway is routing the data to SHM-UCM servers running a geo-spatial patch health assessment and prediction algorithm. The inputs of the prediction algorithm are geometrical variables, environmental variables, and payloads. The proposed SHM-UCM is unique in terms of its capability to manage heterogeneous SHM resources. This has been tested in a case study on Qatar University (QU) in Doha Qatar, where it looked at where SHM nodes are distributed along with occupancy density in each building. This information was taken from QU routers and zone calculation models and were then compared to ideal SHM system data. Results show the effectiveness of the proposed model in logging and dynamically planning SHM. © 2019 by the authors. Licensee MDPI, Basel, Switzerland.en_US
dc.description.sponsorship"Qatar National Research Fund Qatar Foundation"en_US
dc.identifier.citationTariq, H., Tahir, A., Touati, F., Al-Hitmi, M. A. E., Crescini, D., & Manouer, A. B. (2019). Geographical area network-structural health monitoring utility computing model. ISPRS International Journal of Geo-Information, 8(3). https://doi.org/10.3390/ijgi803015en_US
dc.identifier.issn22209964
dc.identifier.urihttp://dx.doi.org/10.3390/ijgi8030154
dc.identifier.urihttp://hdl.handle.net/20.500.12519/15
dc.language.isoenen_US
dc.publisherMDPI AGen_US
dc.relationAuthors Affiliations: Tariq, H., Department of Electrical Engineering, College of Engineering, Qatar University, Doha, 2713, Qatar; Tahir, A., Department of Electrical Engineering, College of Engineering, Qatar University, Doha, 2713, Qatar; Touati, F., Department of Electrical Engineering, College of Engineering, Qatar University, Doha, 2713, Qatar; Al-Hitmi, M.A.E., Department of Electrical Engineering, College of Engineering, Qatar University, Doha, 2713, Qatar; Crescini, D., Department of Information Engineering, Brescia University, Brescia, 25121, Italy; Manouer, A.B., Canadian University Dubai, Dubai, United Arab Emirates
dc.relation.ispartofseriesISPRS International Journal of Geo-Information;Vol. 8, no. 3
dc.rightsPermission to reuse the abstract has been secured from MDPI AG
dc.rights.holderCopyright: 2019 by the authors. Licensee MDPI, Basel, Switzerland.
dc.subjectGeographical Area Network (GAN)en_US
dc.subjectInternet of Things (IoT)en_US
dc.subjectStructural Health Monitoring (SHM)en_US
dc.subjectThings as a Service (TaaS)en_US
dc.subjectUtility Computing (UC)en_US
dc.titleGeographical area network-structural health monitoring utility computing modelen_US
dc.typeArticleen_US

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