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August 16, 2025Open Access

AI-Driven Structural Health Monitoring for Early Detection of Fatigue-Induced Failures in High-Rise Buildings

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AI-based techniques improve anomaly detection and preventive maintenance in high-rise building health monitoring.

AI-based structural health monitoring detects fatigue-induced failures in high-rise buildings, enhancing safety and maintenance procedures.
Advanced machine learning and deep learning models showed improved performance over traditional methods, with %accuracy metrics not specified.
Utilization of time series anomaly analysis and image defect identification using the YOLO model significantly aids in monitoring structural integrity.
The findings highlight the potential of AI and deep learning to systematically automate building health assessments, emphasizing the need for modern techniques in engineering.

SHOAG et al. (2025) studied this question.

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