Risks Related to Advanced Bridge Monitoring Technologies

Bridge monitoring has undergone a significant transformation with the integration of advanced technologies, including structural health monitoring systems, Internet of Things sensors, unmanned aerial vehicles, artificial intelligence, and cloud computing. These technologies enable continuous real-time data acquisition, processing, and early detection of structural degradation. However, their deployment also introduces a range of emerging risks that require careful consideration. This paper presents descriptive risk listings and proposes a comprehensive risk-governance framework for advanced bridge monitoring using the SWOT analysis. The framework integrates a unified risk taxonomy and assessment that links sensor and AI performance with cyber threat modeling and data governance requirements. The application of two real deployments, the Jindo Bridge SHM program and the Stava Bridge digital-twin implementation, shows how the framework converts heterogeneous measurements for improving bridge lifecycle management with the implementation of advanced monitoring technologies. Compared with prior studies that primarily catalog risks, the contribution of the paper is an interdisciplinary, operationalizable method that couples reliability, security, and governance into a single process, thereby ensuring that advanced technologies enhance, rather than erode, the safety and resilience of bridge infrastructure.