From surveillance to incident detection
The Dwarka Expressway emerged last year as India’s first AI-enabled corridor. Spanning 56.46 km, it includes a 5.1-km, eight-lane urban road tunnel. Its digital infrastructure supports real-time monitoring and incident detection, enabling authorities to identify accidents, stalled vehicles and other road hazards.
The shift is significant because conventional cameras primarily capture road activity, whereas AI-powered video analytics can interpret live feeds and flag events that may require intervention.
“The real potential of AI on highways lies not merely in monitoring what is happening, but in using real-time video intelligence to detect, interpret and respond to incidents as they unfold,” said Anoop G Prabhu, Co-Founder and CTO of Vehant Technologies.
He added that AI-powered video analytics can process live camera feeds, identify anomalous events, classify incidents and generate alerts with relevant context, helping response teams assess situations faster.
Bengaluru–Mysuru integrates traffic monitoring and enforcement
On the Bengaluru–Mysuru highway, the National Highways Authority of India (NHAI) has deployed an Advanced Traffic Management System (ATMS) using technology from Vehant Technologies. According to the supplied material, the system integrates video incident detection and speed detection with a command-and-control centre to support real-time incident response and traffic management.
This deployment combines two distinct functions: identifying incidents that may disrupt traffic and monitoring vehicle speeds for enforcement and road safety. The integrated control centre provides an operational platform for monitoring and responding to events.
Rajasthan corridors focus on automated violation detection
In Rajasthan, an AI-powered Intelligent Traffic Management System developed in collaboration with Vehant Technologies has been deployed across the Shahjahanpur–Ajmer, Bar–Jodhpur and Sikar–Bikaner highway corridors.
The system enables automated detection of traffic violations, including overspeeding. This highlights a different emphasis from incident detection: using AI to identify violations that can be addressed through traffic enforcement.
Prabhu said India was moving towards an infrastructure model in which intelligence must complement physical infrastructure development. He also highlighted the potential of edge computing, AI-powered video analytics, real-time data processing and integrated command centres to create a more responsive road ecosystem.
The deployments illustrate different applications of intelligent highway management, rather than a single standardised system across every corridor. The next measure of progress will be how effectively these technologies improve incident response, enforcement and road safety, supported by evidence on operational performance and outcomes.