A Comprehensive Review of Structural Health Monitoring for Steel Bridges: Technologies, Data Analytics, and Future Directions
Alaa El-Sisi, Amal Zamrawi, Shimaa Emad
Abstract
Structural Health Monitoring (SHM) of steel bridges is vital for ensuring the longevity, safety, and reliability of critical transportation infrastructure. This review synthesizes recent advancements in SHM technologies and methodologies for steel bridges, highlighting the shift from traditional vibration-based monitoring to data-driven, intelligent systems. It covers core technological themes, including various sensing systems such as wireless sensor networks, fiber optics, and piezoelectric transducers, along with the impact of machine learning, artificial intelligence, and statistical pattern recognition. The paper explores applications for damage detection, such as fatigue life assessment and monitoring of components like expansion joints. Persistent challenges, including deployment costs, data management complexities, and the need for real-world validation, are addressed. The future of SHM lies in integrating diverse sensing technologies with computational analytics, advancing from periodic inspections to continuous, predictive infrastructure management, which enhances bridge safety, resilience, and economic sustainability.