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Bridges and critical infrastructure are vital to communities but are aging, leading to structural deficiencies. This necessitates robust methods for health monitoring and performance evaluation to ensure safety and prevent costly damage. Conventional monitoring techniques have proven insufficient, especially in disaster-prone areas where resilience is key. Therefore, the current research focuses on two areas: improving structural health monitoring (SHM) and non-destructive evaluation (NDE) methods for current infrastructure and developing durable, low-maintenance alternatives for new structures. Effective condition assessment requires fast, accurate, and low-cost data collection. Two primary approaches are sensor-based monitoring and periodic NDE. However, challenges remain, including the high cost and complexity of sensor installation, data management, and the interpretation of a large amount of data. Recent innovations in sensors, data communication, and processing have improved SHM, but further advancements are needed to reduce costs and enhance efficiency. This Special Issue highlights a variety of NDE methods, SHM techniques, and data interpretation algorithms, including new approaches, such as vision-based sensors, load testing, and machine learning for damage detection. The goal is to improve maintenance strategies through better damage detection and structural health insights, ensuring more resilient infrastructure.
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