Northeast Frontier Railway, in collaboration with IIT Guwahati TIDF, is developing DRISHTI — an artificial intelligence-based surveillance system designed to monitor door locking mechanisms in freight wagons. The system leverages computer vision and machine learning algorithms to provide real-time monitoring of wagon doors during loading, transit, and unloading operations.
DRISHTI addresses a longstanding challenge in freight logistics: unauthorized tampering of wagon doors, which leads to pilferage, cargo loss, and safety hazards. The traditional manual inspection model was prone to human error and inadequate for monitoring thousands of wagons across the vast railway network.
The AI system uses cameras mounted at strategic points — including yards, loading docks, and checkpoints — to continuously scan wagon door positions. When the system detects an anomaly, such as an improperly latched door or a tamper event, it immediately sends an alert to the control room and concerned railway staff. This reduces response time from hours (under manual checks) to seconds.
The integration of computer vision with IoT sensors makes the system scalable across Indian Railways' extensive freight network of over 3 lakh wagons. Railway officials have noted that DRISHTI AI aligns with the broader National Rail Plan 2030 goal of increasing freight modal share to 45%.
This development also exemplifies Industry-Academia collaboration under India's National Education Policy 2020 framework, with IIT Guwahati providing the core AI research while Railways provided operational expertise and data. The project is part of the broader Railway Technology Mission to modernize rail freight operations using cutting-edge technologies like AI, ML, and IoT.