Machine Vision AI in Railroad Safety: Advanced Inspection Techniques

Author(s)	Sujith Kumar Kupunarapu
Country	United States
Abstract	This article explores the transformative impact of machine vision AI in railroad safety, focusing on advanced inspection techniques. It examines the integration of technologies such as line scan cameras, LiDAR, and IoT sensors in enabling comprehensive 360-degree inspections of railway infrastructure and rolling stock. The article discusses key innovations in continuous monitoring, data processing, and AI-driven analysis, highlighting their potential to significantly enhance defect detection accuracy, reduce maintenance costs, and prevent accidents. Real-world applications in structural integrity assessment and overhead line inspection are presented, along with an analysis of current challenges and future developments in the field. The article underscores the paradigm shift from reactive to proactive maintenance strategies, promising a safer and more efficient future for rail transport.
Keywords	Keywords: Machine Vision AI, Railroad Safety, IoT Sensors, Predictive Maintenance, Edge Computing
Field	Computer
Published In	Volume 6, Issue 6, November-December 2024
Published On	2024-11-06
Cite This	Machine Vision AI in Railroad Safety: Advanced Inspection Techniques - Sujith Kumar Kupunarapu - IJFMR Volume 6, Issue 6, November-December 2024. DOI 10.36948/ijfmr.2024.v06i06.29575
DOI	https://doi.org/10.36948/ijfmr.2024.v06i06.29575
Short DOI	https://doi.org/g8qfw4

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International Journal For Multidisciplinary Research