This study presents a compelling application of distributed acoustic sensing (DAS) for railway safety, leveraging existing infrastructure to address a critical gap in continuous monitoring. The methodology—using pulsed light and scattered light analysis—is technically sound, and the machine learning models demonstrate high accuracy in controlled settings. However, a peer reviewer might flag the limited real-world testing as a key constraint; the transition from lab conditions to high-speed opera...