Geographical area network-structural health monitoring utility computing model

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.

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

Keywords

Geographical Area Network (GAN), Internet of Things (IoT), Structural Health Monitoring (SHM), Things as a Service (TaaS), Utility Computing (UC)

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

DOI