AI-DRIVEN AUTONOMOUS ROBOTIC INSPECTION AND PREDICTIVE MAINTENANCE FRAMEWORK FOR ENHANCING PASSENGER EXPERIENCE AND COMMERCIAL SUSTAINABILITY IN INDIAN RAILWAYS

This AI-driven framework introduces an autonomous robotic system for
real-time inspection and predictive maintenance in Indian Railways, aiming
to boost passenger experience and commercial viability. The system
deploys AI-powered robots equipped with computer vision, sensors, and
machine learning algorithms to scan tracks, carriages, and infrastructure
for defects like cracks, wear, or electrical faults. Predictive analytics
forecast failures using historical data and IoT inputs, enabling proactive
repairs that minimize downtime. Reduces delays and enhances safety
through timely interventions, leading to smoother journeys and higher
satisfaction. Commercial Sustainability Lowers maintenance costs by 20-
30% via optimized scheduling, extends asset life, and supports revenue
growth from reliable services. Robotics operate autonomously via edge
computing for low-latency decisions, with a digital twin for simulations.
Pilot results show 95% accuracy in defect detection, paving the way for
sustainable rail operations in a high-density context.