What question did this study set out to answer?

The aim is to explore how AI, particularly machine learning, neural networks, and computer vision, enhances railway safety.

January 25, 2026Applied SciencesOpen Access

Machine Learning, Neural Networks, and Computer Vision in Addressing Railroad Accidents, Railroad Tracks, and Railway Safety: An Artificial Intelligence Review

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This review highlights AI's role in improving railway safety through advanced technologies, indicating significant advancements in risk mitigation.

The aim is to explore how AI, particularly machine learning, neural networks, and computer vision, enhances railway safety.
Comprehensive review of existing research on AI applications in railway safety.
Analysis of machine learning techniques for risk mitigation and monitoring.
Evaluation of computer vision systems for automated defect detection and obstacle identification.
AI methodologies significantly improve real-time monitoring of track conditions.
Predictive maintenance using AI reduces the likelihood of infrastructure failures.
Automated systems enhance defect detection and minimize human errors in safety assessments.

Frej et al. (2026) studied this question.

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This review highlights AI's role in improving railway safety through advanced technologies, indicating significant advancements in risk mitigation.