Severe compromise is brought to integrity and functionality of the rail systems problems like, inoperable tracks, poor welds and unseen blocking. The inspection methods used presently are extremely time-consuming as they are primarily manual and yield no real-time data about what is happening, particularly towards directions that are way gone and out of reach. The system to be proposed is an drone-based solution for railway track monitoring to detect anomalies like cracks, welding flaws, and blockages in real-time. AI models such as YOLO and high-resolution camera-enabled drones capture data across different environments, and detected problems are geotagged. Hybrid 4G/5G and LoRa network ensures fault-tolerant data transmission. A Real-time dashboard displays and indicates anomalies and actionable insights. The system is better in terms of maintenance efficiency by monitoring the railway precisely, scalable, and reliably.