At the Digi Governance Knowledge Exchange Summit organised by Elets Technomedia and IT Department, Government of Kerala, Shalabh Goel, Managing Director, National Capital Region Transport Corporation (NCRTC) shared his insights.

With the rapid expansion of Namo Bharat stations under NCRTC (National Capital Region Transport Corporation), ensuring commuter safety and efficient station management has become paramount. As part of this transformation, AI-enabled CCTV camera analytics are playing a pivotal role in monitoring, detection, and swift response, making public transport not only smarter but significantly safer.

Gone are the days when CCTV cameras were purely observational tools. While standard surveillance remains a baseline, the real game-changer lies in integrating artificial intelligence with camera systems. This cutting-edge evolution enables stations to transition from passive observation to active incident detection and response in real time.

One primary application of AI-driven camera analytics is crowd detection. During peak hours or special occasions, stations tend to get overcrowded. Real-time analytics can identify excessive crowding, allowing the Operations Control Center (OCC) to take effective measures. These can range from deploying an additional train to temporarily closing entry gates to control congestion. The ability to act immediately based on automatic alerts helps mitigate risks and improve commuter experience.

Another crucial function lies in identifying unauthorized or suspicious behavior. For instance, if individuals are found loitering around the premises or attempting to perform stunts—such as riding escalators in the wrong direction or engaging in hazardous acts—the system can detect these behaviors instantly. These detections prompt alerts so that appropriate security actions can be taken without delay, potentially preventing accidents or safety issues.

The role of camera analytics extends to security threats as well. If individuals breach the boundary areas such as wire ducts, tunnels, or restricted zones, these actions are immediately flagged. Similarly, unattended objects — which might trigger bomb scares or could simply be lost items — are swiftly identified. This allows response teams to assess and act promptly, minimizing any threat to public safety.

AI-assisted camera systems are also instrumental in drastically improving service quality. At Namo Bharat stations, an average of 10 to 12 lost item cases are resolved daily with the help of these analytics. Items left behind are often returned efficiently to their rightful owners, thanks to the image recognition and real-time tracking features of AI-powered surveillance.

The feedback from commuters has been overwhelmingly positive, highlighting the trust and relief these systems bring. The integration of AI with surveillance tech is not just an upgrade in infrastructure—it’s an evolution in how public spaces adapt to the increasing demands of safety, efficiency, and technology-led convenience.

As more transport stations follow suit and adopt this technology, the emphasis remains on evolving with commuters’ needs while prioritizing safety and operational excellence through innovation.

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