Framework for a practical and cost-effective IoT-enhanced structural health monitoring and damage diagnostics system with digital twinning
dc.contributor.author | Huang, Jack | |
dc.contributor.author | Broekman, Andre | |
dc.contributor.author | Markou, George | |
dc.contributor.author | Chen, Hua-Peng | |
dc.contributor.email | george.markou@up.ac.za | |
dc.date.accessioned | 2025-09-18T09:21:35Z | |
dc.date.available | 2025-09-18T09:21:35Z | |
dc.date.issued | 2025-08 | |
dc.description | DATA AVAILABILITY : Some or all data, model, or codes that support the findings of this study are available from the corresponding author upon reasonable request. | |
dc.description.abstract | Structural Health Monitoring (SHM) has emerged as a viable alternative to traditional visual and non-destructive assessment methods for civil infrastructure. The integration of sensor systems, the Internet of Things (IoT), and advanced data processing has further digitised SHM, leading to the development of Digital Twin (DT) technology, enabling dynamic, real-time simulations for proactive risk prediction and asset management. However, many existing DT-based SHM systems are costly, complex, and resource-intensive, limiting their practicality for small-scale implementations. This study investigates the feasibility of a practical and cost-effective SHM framework enhanced by DT technology for civil infrastructure. The hardware system explored two low-cost displacement sensors: a potentiometer contact sensor and an infrared non-contact sensor. During the static load testing, the potentiometer demonstrated high accuracy and stability, whilst the infrared sensor, despite higher noise, was effective for submillimetre measurements. These sensors were integrated with an IoT-enabled Arduino Nano 33 microcontroller for remote access via the cloud platform. The software system, “ReConTwin”, developed using open-source resources, provides near real-time updates, analysis, and damage diagnosis through an automated post-processing system. The calibrated DT replicated the force–displacement response, accurately estimated the applied load, and closely predicted mid-span strain and crack formations of a Reinforced Concrete (RC) beam specimen subjected to short-term static three-point bending loads in a controlled laboratory setting. The user-friendly design and compatibility with standard commercial computers enhance the accessibility and feasibility of the proposed DT-SHM framework, making it a promising scalable solution for widespread adoption in real-world civil infrastructure applications. | |
dc.description.department | Civil Engineering | |
dc.description.librarian | hj2025 | |
dc.description.sdg | SDG-09: Industry, innovation and infrastructure | |
dc.description.sponsorship | Funding provided by the China/South Africa project and support from the University of Pretoria’s Department of Civil Engineering. Open access funding provided by University of Pretoria. | |
dc.description.uri | https://link.springer.com/journal/13349 | |
dc.identifier.citation | Huang, J., Broekman, A., Markou, G. et al. Framework for a practical and cost-effective IoT-enhanced structural health monitoring and damage diagnostics system with digital twinning. Journal of Civil Structural Health Monitoring 15, 2059–2084 (2025). https://doi.org/10.1007/s13349-025-00927-9. | |
dc.identifier.issn | 2190-5452 (print) | |
dc.identifier.issn | 2190-5479 (online) | |
dc.identifier.other | 10.1007/s13349-025-00927-9 | |
dc.identifier.uri | http://hdl.handle.net/2263/104387 | |
dc.language.iso | en | |
dc.publisher | Springer | |
dc.rights | © The Author(s) 2025. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License. | |
dc.subject | Structural health monitoring (SHM) | |
dc.subject | Internet of Things (IoT) | |
dc.subject | Digital twin | |
dc.subject | Sensors | |
dc.subject | Low-cost alternative | |
dc.subject | Damage diagnostics | |
dc.title | Framework for a practical and cost-effective IoT-enhanced structural health monitoring and damage diagnostics system with digital twinning | |
dc.type | Article |