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ArticleOpen Access http://dx.doi.org/10.26855/cebs.2025.06.002

Predictive Structural Health Monitoring for Large Bridges Using Sensors

Santanu Palit1,*, Md Akib2, Suchayan Chakraborty Shoumik3, Md. Ahsan Habib4

1Roads and Highways Department, Bridge Maintenance Programming Division, Dhaka 1000, Bangladesh.

2Department of Civil Engineering, Southern University Bangladesh, Chattogram 4000, Bangladesh.

3Department of Civil Engineering, Leading University, Sylhet 3100, Bangladesh.

4Roads and Highways Department, SASEC Road Connectivity Project-2, Dhaka 1000, Bangladesh.

*Corresponding author: Santanu Palit


Published: July 29,2025

Abstract

Bangladesh is a developing country where bridges are a crucial part for daily transportation. Unfortunately, Bangladesh's geological location makes it a hotspot for various natural calamities which can eventually compromise the lon-gevity of various infrastructures over time. Therefore, structural health monitor-ing becomes a crucial factor for improving the longevity of structures and avoid-ing disasters of large magnitudes. Thanks to the emerging advancements in technology, there are various tools and sensors which allows for monitoring of specific factors which can help predict distress within a structure. Such integration can help engineers to monitor the conditions of structures and can allow them to intervene at the correct time to avoid collapse and further damage. The case studies reviewed in this research paper which used predictive structural health monitoring solutions like the Geumdand Bridge of South Korea and the Tamar Bridge in United Kingdom (UK) showed significant improvement of longevity, safety and condition monitoring. With the correct integration of appropriate structural health monitoring sensors like tilt sensors, orientation sensors, strain sensors, temperature sensors etc. can gather appropriate data which can be pro-cessed using a capable machine learning algorithm like Random Forest or similar algorithm to give accurate readings of structural integrity status and give early warnings regarding possibilities of a structural collapse. This research papers ex-plores this integration in a more dynamic manner by integration an EWS system and hopefully sheds light in the importance of structural health monitoring for large complex bridges and implementation of an early warning system (EWS).

Keywords

Structural Health Monitoring (SHM); Early Warning System (EWS); Structural integrity; Machine learning algorithm; Structural integrity; Transportation; Public safety; Random Forest (RF); IoT (Internet of Things) sensors; Thermal stress; Pre-dictive maintenance; Bridges; Dynamic monitoring

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How to cite this paper

Predictive Structural Health Monitoring for Large Bridges Using Sensors

How to cite this paper: Santanu Palit, Md Akib, Suchayan Chakraborty Shoumik, Md. Ahsan Habib. (2025). Predictive Structural Health Monitoring for Large Bridges Using Sensors. Civil Engineering & Building Science, 2(1), 9-20.

DOI: http://dx.doi.org/10.26855/cebs.2025.06.002

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