Virtual Booth

Railway safety is critically dependent on the timely detection of infrastructure defects such as rail curvature and surface cracks, which can lead to derailments and severe accidents if left unaddressed. Traditional inspection methods are manual, time-consuming, and prone to human error, making them inadequate for modern, high-demand rail systems. This study presents Smart Rail Safety, an intelligent monitoring system that integrates infrared sensors with artificial intelligence (AI) to enable continuous, real-time detection of rail curvature and surface cracks. The system’s dual-detection capability addresses both gradual deformations and sudden crack formations, while AI-powered analytics enhance accuracy and minimize false positives. Smart alerts provide timely, actionable insights for rapid intervention, reducing inspection delays and maintenance costs. Experimental results demonstrate robust performance across varying environmental conditions, with significant improvements in detection speed and reliability compared to conventional methods. Although large-scale field validation remains necessary, findings highlight the system’s scalability, affordability, and potential for predictive maintenance. By bridging advanced sensing with intelligent decision support, Smart Rail Safety offers a proactive pathway toward safer, smarter, and more resilient railway infrastructure.