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Framework for a practical and cost-effective IoT-enhanced structural health monitoring with digital twinning

Dissertation (MEng (Structural Engineering))--University of Pretoria, 2024.

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Other Authors: Markou, George
Format: Thesis
Language:English
Published: University of Pretoria 2025
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author2 Markou, George
author_browse Markou, George
author_facet Markou, George
collection Thesis
dc_rights_str_mv © 2023 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria.
description Dissertation (MEng (Structural Engineering))--University of Pretoria, 2024.
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institution University of Pretoria (South Africa)
language English
last_indexed 2026-06-10T12:40:21.476Z
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provenance_str_mv Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository
publishDate 2025
publishDateRange 2025
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spelling oai:repository.up.ac.za:2263/101155 Framework for a practical and cost-effective IoT-enhanced structural health monitoring with digital twinning Markou, George jackhuang0824@hotmail.com Broekman, André Huang, Jack Structural health monitoring Digital twin IoT Low-cost displacement sensors Damage diagnostics Dissertation (MEng (Structural Engineering))--University of Pretoria, 2024. The South African civil infrastructure is critical for passenger and freight transit, connecting major cities and ports. Despite state owned investment efforts aimed at maintaining and improving existing infrastructure, it continues to deteriorate rapidly. This degradation negatively impacts the commercial sector and diminishes the country's global economic competitiveness. With increasing traffic volumes to meet escalating transport demands, effective condition assessment and maintenance of existing civil infrastructure are paramount. Currently, the industry primarily relies on visual inspections, which are useful for identifying visible issues but are subjective, inconsistent, and unable to detect internal problems. Other non-destructive methods exist but are often costly, labour intensive, complex and disruptive to operations. These challenges highlight the urgent need for advanced, automated, and timely monitoring approaches to ensure infrastructure integrity, support economic growth, and promote infrastructure sustainability. The Fourth Industrial Revolution has introduced advanced smart technologies and data driven solutions, significantly impacting civil infrastructure management. A critical area within this development is Structural Health Monitoring (SHM), which provides stakeholders with valuable insights into infrastructure conditions. The integration of sensor systems, the Internet of Things (IoT), and advanced data processing has led to the concept of Digital Twins (DTs). DTs offer dynamic, real time simulations of structural behaviours, aiding in proactive asset management by predicting potential risks and formulating maintenance strategies. However, current DT based SHM systems often involve prohibitive costs, complex data processing, and demanding computing systems and power, making them impractical and financially unfeasible, especially for small scale implementations. Additionally, many existing systems lack user-friendly interfaces and interpretability, reducing user confidence and comprehension. This study aims to establish a practical and cost effective SHM framework enhanced by DT technology for civil infrastructure. The primary objectives include demonstrating that affordable contact and non contact sensors can provide precise and reliable results for DT enhanced SHM frameworks, proving that cost effective microcomputing hardware with IoT capability can enable efficient, near real time data transmission from physical structures to digital models, and developing a practical, comparatively simple numerical DT model to simulate the mechanical behaviour of Reinforced Concrete (RC) structures. The experimental study performed for this research work successfully developed a DT based SHM prototype capable of digitally replicating the mechanical response of a RC beam. It introduced two novel low cost sensors: a potentiometer contact sensor, and an Infrared (IR) non contact sensor. The potentiometer sensor demonstrated excellent accuracy compared to the LVDT control, with an overall absolute error of 41.2 μm, an overall percentage error of 11.2%, and high stability (overall standard deviation of 37.9 μm), making it ideal for precise measurements. In contrast, the IR sensor, tested within a detection range of 50 mm to 70 mm, exhibited lower accuracy with an overall absolute error of 184.8 μm and percentage error of 202.2%, and greater variability (overall standard deviation of 211.7 μm). Despite higher noise levels, the IR sensor effectively detected sub-millimetre displacements. The hardware system, integrating these low-cost sensors with an IoT-enabled Arduino microcontroller and a custom software program, “ReConTwin,” featured an automated post-processing system for near real-time model updates, analysis, and damage diagnosis. The calibrated DT accurately estimated imposed loads with an average absolute error of 2.11 kN and relative error of 11.6%, and predicted strain with an average absolute error of 281 με and relative error of 34.3%, providing reliable insights into the monitored beam’s structural behaviour. The user friendly design and compatibility with standard commercial computers significantly enhance the accessibility and feasibility of the proposed DT SHM framework for widespread adoption. The study demonstrates the potential of practical and affordable DT enhanced SHM systems, making them more accessible for scalable, real world civil infrastructure applications. China/South Africa project (Reference: CHIN2002255 06754, UID: 132787) Civil Engineering MEng (Structural Engineering) Unrestricted Faculty of Engineering, Built Environment and Information Technology SDG-09: Industry, innovation and infrastructure 2025-02-22T10:57:38Z 2025-02-22T10:57:38Z 2025-04 2024-08 Dissertation * A2025 http://hdl.handle.net/2263/101155 DOI: https://doi.org/10.25403/UPresearchdata.28464131.v1 Available Upon Reasonable Request en © 2023 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. application/pdf University of Pretoria
spellingShingle Structural health monitoring
Digital twin
IoT
Low-cost displacement sensors
Damage diagnostics
Framework for a practical and cost-effective IoT-enhanced structural health monitoring with digital twinning
title Framework for a practical and cost-effective IoT-enhanced structural health monitoring with digital twinning
title_full Framework for a practical and cost-effective IoT-enhanced structural health monitoring with digital twinning
title_fullStr Framework for a practical and cost-effective IoT-enhanced structural health monitoring with digital twinning
title_full_unstemmed Framework for a practical and cost-effective IoT-enhanced structural health monitoring with digital twinning
title_short Framework for a practical and cost-effective IoT-enhanced structural health monitoring with digital twinning
title_sort framework for a practical and cost effective iot enhanced structural health monitoring with digital twinning
topic Structural health monitoring
Digital twin
IoT
Low-cost displacement sensors
Damage diagnostics
url http://hdl.handle.net/2263/101155