Conventional and Emerging Methods in Structural Monitoring: Bridging the Past and Future

Dear Colleagues,

Structural monitoring is crucial for ensuring the safety, durability, and resilience of civil infrastructure, including bridges, buildings, dams, and tunnels. While traditional methods (e.g., strain gauges and accelerometers) have long been the backbone of structural health monitoring (SHM), rapid advancements in sensing technologies, data analytics, and automation are revolutionizing the field. Many industries still depend on traditional systems due to their reliability; however, innovative techniques (e.g., computer vision, wireless sensor networks, and digital twins) offer unprecedented precision, scalability, and cost efficiency. The rise of AI/ML, IoT, and big data analytics has enabled predictive maintenance and real-time decision-making. This Special Issue seeks to critically examine the synergies and trade-offs between conventional and emerging approaches, fostering a multidisciplinary dialogue to address pressing challenges in infrastructure resilience, sustainability, and safety.

Potential topics for this issue include, but are not limited to, the following:

• Traditional techniques: strain gauges, accelerometers, and manual visual inspections.
• Innovative solutions: computer vision, drone-based inspections, optical fiber sensors, IoT-enabled networks, and AI-driven damage detection.
• Hybrid approaches: integration of traditional systems with emerging technologies.
• Case studies: real-world applications demonstrating reliability and cost-effectiveness.

Dr. Tengjiao Jiang
Dr. Shaorui Wang
Dr. Junlin Heng
Dr. Ming Wang
Dr. Kui Luo
Guest Editors

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