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To develop an automated system for the early detection of railway track faults using image processing and fuzzy logic.

April 16, 2026Open Access

Smart Railway Track Monitoring System Using Image Processing And Fuzzy Logic For Early Fault Detection

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To develop an automated system for the early detection of railway track faults using image processing and fuzzy logic.
Utilized image processing techniques for capturing and analyzing railway track images.
Employed preprocessing methods like grayscale conversion and noise filtering to enhance image quality.
Applied edge detection and thresholding techniques to identify cracks and abnormalities on the track surface.
Developed a fuzzy logic-based decision support system to improve classification accuracy.
Successfully identified railway track faults with high accuracy, reducing false detections.
Demonstrated the capability for real-time monitoring and early warning for maintenance teams.
Significantly minimized the need for manual inspections, enhancing efficiency in maintenance strategies.

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Automated framework detects track faults in railway systems, suggesting improved safety and maintenance efficiency.

Sai et al. (2026) studied this question.

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