Intelligent Acoustic Sensing and Edge AI for Structural Health Monitoring and Non-destructive Evaluation

Acoustic sensing technologies, including acoustic emission, ultrasonic testing, and emerging magneto-acoustic approaches, are widely used in structural health monitoring (SHM) and non-destructive evaluation (NDE) for infrastructure, industrial systems, and smart environments. These techniques provide sensitive and physics-grounded measurements capable of detecting early-stage damage, stress evolution, and material degradation. With the rapid development of intelligent signal processing, machine learning, and embedded computing platforms, acoustic monitoring is transitioning from offline analysis toward autonomous, real-time, and distributed diagnostic systems. Recent advances in artificial intelligence and edge computing have further expanded the potential of acoustic sensing. Intelligent algorithms can now extract complex patterns from noisy signals, while lightweight models and IoT architectures enable deployment directly on sensing nodes. However, challenges remain in signal robustness, physical interpretability, scalable deployment, and the integration of sensing physics with data-driven models. This Research Topic aims to provide a comprehensive platform for recent advances in intelligent acoustic sensing methods, signal interpretation techniques, and deployable monitoring systems. The collection seeks to bridge fundamental acoustic measurement science, intelligent diagnostic algorithms, and real-world system implementation. Both methodological innovations and application-driven studies are encouraged, particularly those demonstrating how acoustic sensing can be transformed into reliable, scalable, and intelligent monitoring solutions. Topics of interest include, but are not limited to:• Acoustic emission–based structural health monitoring and fault diagnosis• Ultrasonic and magneto-acoustic non-destructive testing methods• Stress measurement and material characterization using acoustic signals• Intelligent signal processing and feature extraction for acoustic data• Machine learning and deep learning for acoustic diagnosis and monitoring• Edge AI, embedded systems, and IoT architectures for acoustic sensing• Distributed sensing networks and autonomous monitoring platforms• Multimodal sensing and data fusion involving acoustic signals• Physics-informed or interpretable models for acoustic diagnostics• Applications in infrastructure monitoring, industrial maintenance, energy systems, transportation, and smart agricultureWe welcome submissions of Original Research Articles, Methods papers, Reviews, Perspectives, and Case Studies that present theoretical advances, methodological innovations, experimental validations, or real-world deployment results. Interdisciplinary contributions combining acoustic sensing physics, intelligent algorithms, and system-level implementation are particularly encouraged. By bringing together contributions from both academia and industry, this Research Topic aims to advance the development of intelligent acoustic monitoring technologies and promote their transition from laboratory research to practical, large-scale deployment. Topic editors: Yuxuan Zhang, Zenghua Liu, Xiaoran Wang Source: https://www.frontiersin.org/research-topics/78878/intelligent-acoustic-sensing-and-edge-ai-for-structural-health-monitoring-and-non-destructive-evaluation