The 149th Lord Jagannath Rath Yatra began in Ahmedabad with a high-tech security operation involving AI surveillance and thousands of personnel.

The scale of the security measures reflects the sensitivity of the religious event and the need to manage massive crowds across the city's urban core. Officials said they aim to ensure the smooth conduct of the procession and prevent potential disruptions.

Union Home Minister Amit Shah and Gujarat Chief Minister Bhupendra Patel joined the festivities at the Jagannath Temple in Jamalpur. The security plan includes the deployment of over 30,000 security personnel [1] to manage the crowds and maintain order.

To monitor the route, authorities installed over 3,500 CCTV cameras, which includes 1,300 newly added units [2]. These cameras are integrated with AI-driven surveillance to identify potential threats in real time. The security apparatus also includes the use of drones and GPS-tracked elephants to monitor the movement of the procession.

The route for the Yatra covers a distance of between 14 [2] and 16 km [1] through the city. Police and security forces have established a perimeter to protect the 200 processions involved in the event. DGP G.S. Malik and the Ahmedabad Police are overseeing the operation to ensure public safety throughout the journey.

Chief Minister Bhupendra Patel led the event with a focus on combining traditional devotion with modern technology. The integration of GPS and AI represents a significant shift in how the city manages large-scale religious gatherings.

The 149th Lord Jagannath Rath Yatra began with high-tech security measures, including AI-driven surveillance.

The deployment of AI-driven surveillance and GPS tracking for the Rath Yatra signals a broader trend of 'smart policing' in India's urban centers. By integrating high-density CCTV networks with real-time AI analytics, Gujarat authorities are attempting to mitigate the inherent risks of large-scale public gatherings in densely populated areas, shifting from reactive crowd control to predictive monitoring.