Geographical area network-structural health monitoring utility computing model

dc.contributor.author Tariq, Hasan
dc.contributor.author Tahir, Anas
dc.contributor.author Touati, Farid
dc.contributor.author Al-Hitmi, Mohammed Abdulla E.
dc.contributor.author Crescini, Damiano
dc.contributor.author Mnaouer, Adel Ben
dc.date.accessioned 2020-01-23T11:57:20Z
dc.date.available 2020-01-23T11:57:20Z
dc.date.copyright 2019 en_US
dc.date.issued 2019
dc.description This 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/ijgi803015 en_US
dc.description.abstract In 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.citation Tariq, 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/ijgi803015 en_US
dc.identifier.issn 22209964
dc.identifier.uri http://dx.doi.org/10.3390/ijgi8030154
dc.identifier.uri http://hdl.handle.net/20.500.12519/15
dc.language.iso en en_US
dc.publisher MDPI AG en_US
dc.relation Authors 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.ispartofseries ISPRS International Journal of Geo-Information;Vol. 8, no. 3
dc.rights Permission to reuse the abstract has been secured from MDPI AG
dc.rights.holder Copyright: 2019 by the authors. Licensee MDPI, Basel, Switzerland.
dc.subject Geographical Area Network (GAN) en_US
dc.subject Internet of Things (IoT) en_US
dc.subject Structural Health Monitoring (SHM) en_US
dc.subject Things as a Service (TaaS) en_US
dc.subject Utility Computing (UC) en_US
dc.title Geographical area network-structural health monitoring utility computing model en_US
dc.type Article en_US
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