The new AI-based surveillance system, developed in collaboration with IIT Guwahati, aims to eliminate manual checks and provide real-time status updates on wagon security, saving hours of manpower per train
Indian Railways is piloting a new, advanced artificial intelligence-based surveillance system designed to enhance freight security and streamline operations across its vast network. The system, named DRISHTI (AI-based Locking Monitoring System), is being introduced to combat the operational challenge of detecting unlocked or tampered doors on moving freight wagons.
The innovation promises a massive leap in efficiency, capable of generating status reports on wagon lock conditions in just 30 to 35 seconds.
Autonomous Monitoring Halves Inspection Time
The current process for inspecting freight security is described by railway officials as time-consuming and manpower-intensive. According to Kapinjal Kishore Sharma, Chief Public Relations Officer for Northeast Frontier Railways (NFR), checking a goods train of 58 wagons manually requires three to four RPF (Railway Protection Force) personnel and takes between half an hour to one hour.
The AI-based system eliminates this friction. “It is a fast system that completes a wagon checking within 30 to 35 seconds and generates accurate status reports,” Sharma confirmed. “It will save manpower and time… Traditional manual checks are often impractical for long-haul rakes under dynamic conditions.”
The system integrates high-speed imaging, computer vision, and machine learning to provide real-time status updates and automatically detect abnormal events or tampering during transit, even working seamlessly during inclement weather.
Indigenous Innovation & Future Rollout
DRISHTI is the result of a collaborative initiative between the Northeast Frontier Railway (NFR) and the Indian Institute of Technology Guwahati Technology Innovation and Development Foundation (IITG TIDF). The partnership aimed to create an intelligent, real-time solution capable of autonomously flagging anomalies in door locking mechanisms using advanced computer vision algorithms.
The railway official stated that initial trials have been successful, validating the potential of the indigenous innovation.
“Another trial at a larger level will be conducted very soon,” Sharma explained. “Once it gets reliable success, the system will be rolled out at different stations.”
This implementation marks a significant step toward modernising rolling stock safety and operational reliability across the Indian rail network, leveraging AI to shift from reactive monitoring to predictive, real-time defence against security threats.
