Machine Learning-Enhanced Fiber Optic Sensing: From Materials to Applications

Dear Colleagues,

Fiber optic sensing technologies have become key tools in a wide range of applications, from structural health monitoring and materials testing to biomedical diagnostics and environmental monitoring. With the rapid development of machine learning (ML) and artificial intelligence (AI), there are now new opportunities to enhance the performance, sensitivity, and versatility of fiber optic sensors.

This Special Issue will cover advances in machine learning-enhanced fiber optic sensing, including novel sensor materials and designs, innovative uses of existing sensors, and the application of ML-based signal processing to improve measurement accuracy and enable real-time data interpretation. We are seeking contributions that focus on topics of interest in this area, which include, but are not limited to, new fiber-based sensor concepts, integration of ML algorithms with distributed sensing techniques, data-driven noise reduction, predictive maintenance, and evaluation of ML-enhanced sensing systems in real-world environments. Both original research and review papers are welcome.

Dr. Boguslaw Szczupak
Dr. Mateusz Mądry
Guest Editors

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