IOT-BASED STRUCTURAL HEALTH MONITORING FRAMEWORK FOR LONG-SPAN BRIDGE SAFETY AND MAINTENANCE
Abstract
Long-span bridges are strategic infrastructure assets because they connect cities, ports, logistics corridors, industrial zones and emergency routes. Their large scale, complex structural geometry, dynamic loading, wind exposure, corrosion risk and climate sensitivity require continuous and intelligent monitoring rather than periodic visual inspection alone. This strengthened review examines how Internet of Things (IoT) technologies support structural health monitoring (SHM) for long-span bridge safety and maintenance. A PRISMA-informed methodology was applied to screen studies published from 2020 to 2025 across Scopus, Web of Science, IEEE Xplore, ScienceDirect, SpringerLink and other engineering databases. From 450 initially identified records, 30 studies were selected for detailed synthesis after duplicate removal, screening and eligibility assessment. The review evaluates sensing technologies, wireless communication protocols, edge and cloud platforms, artificial intelligence, digital twins, BIM integration and predictive maintenance. It also introduces a quantitative technology-occurrence analysis, a communication-protocol comparison matrix, three real bridge case studies and a Saudi Vision 2030 alignment section. The proposed framework integrates IoT sensors, LoRaWAN, edge computing, cloud analytics, AI, digital twins, BIM and a maintenance decision engine for Saudi smart bridges. Findings indicate that IoT-enabled SHM can improve damage detection, reduce unplanned closures, support maintenance prioritization and increase infrastructure resilience. However, technical barriers remain in sensor drift, false alarms, cybersecurity, data quality, energy supply, interoperability, capital cost and model explainability. The paper contributes a holistic review and conceptual framework linking bridge SHM to smart infrastructure, intelligent transportation systems and sustainable mega-project delivery in Saudi Arabia.