A complete Internet of Things (IoT) platform for Structural Health Monitoring (SHM)

Mahmud, Anam; Bates, Kyle; Wood, Trent; Abdelgawad, Ahmed; Yelamarthi, Kumar

doi:10.1109/wf-iot.2018.8355094

Cited by 69 publications

(30 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Structural health monitoring technologies based on imaging and vision sensors [10,11], and microelectromechanical systems (MEMS) sensors [12,13] can be considered as emerging technologies [14]. Application of wireless sensor network [15,16] for the condition assessment has evolved to internet of things (IOT) [17,18] based structural health monitoring system.…”

Section: Introductionmentioning

confidence: 99%

Development of a Structural Monitoring System for Cable Bridges by Using Seismic Accelerometers

Jeong

Jang

Nam³

et al. 2020

Applied Sciences

View full text Add to dashboard Cite

In this study, a structural health monitoring system for cable-stayed bridges is developed. In the system, condition assessment of the structure is performed based on measured records from seismic accelerometers. Response indices are defined to monitor structural safety and serviceability and derived from the measured acceleration data. The derivation process of the indices is structured to follow the transformation from the raw data to the final outcome. The process includes, noise filtering, baseline correction, numerical integration, and calculation of relative differences. The system is packed as a condition assessment program, which consists of four major process of the structural health evaluation: (i) format conversion of the raw data, (ii) noise filtering, (iii) generation of response indices, and (iv) condition evaluation. An example set of limit states is presented to evaluate the structural condition of the test-bed cable-stayed bridge.

show abstract

Section: Introductionmentioning

confidence: 99%

Development of a Structural Monitoring System for Cable Bridges by Using Seismic Accelerometers

Jeong

Jang

Nam³

et al. 2020

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…In SHM, interorganizational sharing of SHM data is complex, untrusted, and less-reliable for transparency. Nonetheless, recently, many researchers [19,20] have introduced IoT-cloud based systems for SHM. Still, there is a lack of trust and transparency for interorganizational sharing of data.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Blockchain and Internet-of-Things Network for Underground Structure Health Monitoring

Khan

Lee

2018

Sensors

View full text Add to dashboard Cite

The Internet-of-things (IoT) and blockchain are growing realities of modern society, and both are rapidly transforming civilization, either separately or in combination. However, the leverage of both technologies for structural health monitoring (SHM) to enable transparent information sharing among involved parties and autonomous decision making has not yet been achieved. Therefore, this study combines IoT with blockchain-based smart contracts for SHM of underground structures to define a novel, efficient, scalable, and secure distributed network for enhancing operational safety. In this blockchain-IoT network, the characteristics of locally centralized and globally decentralized distribution have been activated by dividing them into core and edge networks. This division enhances the efficiency and scalability of the system. The proposed system was effective in simulation for autonomous monitoring and control of structures. After proper design, the decentralized blockchain networks may effectively be deployed for transparent and efficient information sharing, smart contracts-based autonomous decision making, and data security in SHM.

show abstract

“…Deep Learning (DL) has been implemented on raspberry pi but still needs improvement for cloud compatibility and pairing with mathematical techniques mentioned in [24]. We believe that the role of SHM is very vital in reporting disasters and handling any abnormal and hazardous condition using seismic waves analysis through several signal processing algorithms, i.e., Frequency Domain Decomposition (FDD) and Eigen System Realization Algorithm (ERA), as defined in Reference [25][26][27][28]. Nonetheless, a multi-layer interoperable algorithm is required that can take multiple variables and output multiples decisions based on required solutions at edge (private cloud) and GAN (public cloud) level.…”

Section: Introductionmentioning

confidence: 99%

Geographical Area Network—Structural Health Monitoring Utility Computing Model

Tariq

Tahir

Touati

et al. 2019

IJGI

View full text Add to dashboard Cite

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.

show abstract

A complete Internet of Things (IoT) platform for Structural Health Monitoring (SHM)

Cited by 69 publications

References 15 publications

Development of a Structural Monitoring System for Cable Bridges by Using Seismic Accelerometers

Development of a Structural Monitoring System for Cable Bridges by Using Seismic Accelerometers

Hybrid Blockchain and Internet-of-Things Network for Underground Structure Health Monitoring

Geographical Area Network—Structural Health Monitoring Utility Computing Model

Contact Info

Product

Resources

About