Advanced Sensing and Deep Learning for Damage Detection and Performance Assessment in Structural Health Monitoring
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Fault Diagnosis & Sensors".
Deadline for manuscript submissions: 15 February 2026 | Viewed by 58
Special Issue Editors
Interests: structural health monitoring; resilient and intelligent infrastructure; AI for infrastructure
Special Issues, Collections and Topics in MDPI journals
Interests: structural health monitoring; sustainable construction materials; seismic resilient structures
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Structural Health Monitoring (SHM) has rapidly developed over the past few decades as authorities and practitioners look for new, efficient methods to ensure the safety and longevity of critical infrastructure. Recent advancements in sensor and computing technologies have significantly improved the ability to capture detailed data on structural conditions. When combined with the power of state-of-the-art artificial intelligence techniques, these technologies can provide unprecedented insights into the health and performance of engineering structures. With an ability to learn complex patterns and make accurate predictions, deep learning models are particularly well-suited for analyzing the vast amounts of data generated by modern sensor systems.
To cater for the need of the scientific community, we invite original research and comprehensive review articles that explore innovative approaches to damage detection and performance assessment using advanced sensing and deep learning. The topics of interest include, but are not limited to, sensing techniques, edge computing, data fusion, and the latest application of deep neural networks. Contributions that address the challenges and opportunities in integrating these technologies in real-world scenarios are particularly encouraged. By bringing together cutting-edge studies from around the globe, this Special Issue aims to capture the transformative applications in SHM and provide the reader with the latest insights into this fascinating realm of engineering research.
Dr. Andy Nguyen
Dr. Yang Yu
Guest Editors
Manuscript Submission Information
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Keywords
- structural health monitoring
- advanced sensing
- deep learning
- damage detection
- performance assessment
- smart inspection
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