Integration of Machine Vision-Based Inspection Systems (MVIS) with Automated Maintenance Systems for Optimizing Resource Allocation in Indian Railways

Author(s)	Yashasvi Saraff
Country	India
Abstract	Indian Railways, one of the largest and busiest rail networks in the world, faces immense challenges in maintaining its infrastructure and rolling stock. Manual inspections, though historically reliable, are slow, labour-intensive, and prone to human error. Machine Vision-Based Inspection Systems (MVIS), enhanced with Artificial Intelligence (AI), present an opportunity to transform railway maintenance by enabling real-time defect detection, predictive analytics, and optimized resource allocation. This paper explores the integration of MVIS with automated maintenance systems, examining its technological underpinnings, potential applications, compliance with Research Designs and Standards Organisation (RDSO) norms, and applicability in India’s pursuit of high-speed rail. Through a review of literature, case studies, system design frameworks, and reference to recent Indian pilot projects, we propose a roadmap for deploying MVIS across Indian Railways, ensuring efficiency, safety, and sustainability.
Keywords	Machine Vision, Automated Railway Maintenance, Defect Detection, Image Processing, Artificial Intelligence, Deep Learning, Railway Safety, Predictive Maintenance, Mechanical Systems, Structural Health Monitoring, Transportation Engineering, Quantum-Inspired Engineering
Field	Physics > Mechanical Engineering
Published In	Volume 7, Issue 5, September-October 2025
Published On	2025-10-31
DOI	https://doi.org/10.36948/ijfmr.2025.v07i05.59158

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