• Jatin M
• V Charan Kumar
• Yashaswini V
• Sharath P C
• K Girish

Rapid advances in Internet of Things (IoT) technologies have opened new avenues for enhancing railway safety and operational intelligence. This paper presents an IoT-Enabled Smart Surveillance Model for Railway Track Anomalies and Passenger Protection, designed to address the perennial challenges of real-time track monitoring and obstacle detection. The proposed framework integrates a distributed network of IoT sensors—including vision-enabled devices, vibration detectors, and environmental sensors—deployed along railway tracks to enable continuous surveillance and instant anomaly recognition. Sensor data are transmitted in real time to a centralised analytical engine, leveraging AI algorithms for multi-modal data fusion, pattern detection, and predictive analytics. The system is capable of detecting foreign objects, track deformation, landslides, and unauthorised access, thereby significantly reducing risks associated with derailments and accidents. Automated alert mechanisms, supported by cloud-based processing, ensure rapid notification to control centres and train operators. Field trials on a test railway segment demonstrated detection accuracy above 95% for various obstacle scenarios and exhibited robust scalability across extended track environments. The framework further showcases energy-efficient sensor node design and secure wireless protocols to safeguard data integrity. This research establishes a foundation for next-generation railway surveillance systems, contributing to both passenger safety and infrastructure resilience. Future work will focus on wider field deployment, sensor optimization, and machine learning enhancement to further advance railway security standards.

Internet of Things (IoT), Railway Safety, Smart Surveillance, Anomaly Detection, Sensor Fusion, Edge Computing, Cloud Analytics, Machine Learning, Zigbee, Predictive Maintenance.

"IoT-Enabled Smart Surveillance Model for Railway Track Anomalies and Passenger Protection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 11, page no.d475-d482, November-2025, Available :http://www.jetir.org/papers/JETIR2511352.pdf

"IoT-Enabled Smart Surveillance Model for Railway Track Anomalies and Passenger Protection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 11, page no. ppd475-d482, November-2025, Available at : http://www.jetir.org/papers/JETIR2511352.pdf