NHAI Deploys AI Dashcam System To Monitor National Highways

01 Jun 2026 CW Team

Advanced artificial intelligence and machine learning models have been deployed to automatically identify more than 30 categories of defects and anomalies. For implementation, states and union territories have been divided into five zones: north, central, east, west and south. A standard operating procedure details the roles and responsibilities of road maintenance divisions and survey agencies for dashcam surveys and highway monitoring.

The primary focus will be pavement conditions, including detection of potholes, rutting and severe cracking, while surveys will also cover road furniture with real-time identification of damaged or faded lane markings, crash barriers and non-functional streetlights. At least one weekly survey will be conducted at night every month to evaluate the performance of signage, pavement markings, road studs and highway lighting. Other maintenance issues such as missing drainage covers, water stagnation, vegetation growth and the condition of bus bays, will be monitored to support timely interventions.

The Ministry of Road Transport and Highways (MoRTH) has shifted attention towards long-term maintenance and protection of highways and initiated a nationwide programme with regular state-wise reviews. As part of the exercise, the ministry is procuring Intelligent Pavement Assessment Vehicles (iPAVe) capable of collecting structural and functional pavement data, and trial runs are underway. The minister reviewed maintenance progress across several states and directed officials to accelerate on-ground execution, ensure timely completion and strengthen monsoon preparedness through drainage and slope protection measures.

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The National Highways Authority of India (NHAI) has identified more than 600 stretches covering nearly 40,000 km of national highways and expressways for assessment using advanced AI-powered Dashcam Analytics Services (DAS). Route Patrol Vehicles (RPVs) fitted with dashboard cameras will conduct comprehensive weekly surveys across the network. The initiative aims to transform operations and maintenance by enabling automated detection of defects and anomalies. Advanced artificial intelligence and machine learning models have been deployed to automatically identify more than 30 categories of defects and anomalies. For implementation, states and union territories have been divided into five zones: north, central, east, west and south. A standard operating procedure details the roles and responsibilities of road maintenance divisions and survey agencies for dashcam surveys and highway monitoring. The primary focus will be pavement conditions, including detection of potholes, rutting and severe cracking, while surveys will also cover road furniture with real-time identification of damaged or faded lane markings, crash barriers and non-functional streetlights. At least one weekly survey will be conducted at night every month to evaluate the performance of signage, pavement markings, road studs and highway lighting. Other maintenance issues such as missing drainage covers, water stagnation, vegetation growth and the condition of bus bays, will be monitored to support timely interventions. The Ministry of Road Transport and Highways (MoRTH) has shifted attention towards long-term maintenance and protection of highways and initiated a nationwide programme with regular state-wise reviews. As part of the exercise, the ministry is procuring Intelligent Pavement Assessment Vehicles (iPAVe) capable of collecting structural and functional pavement data, and trial runs are underway. The minister reviewed maintenance progress across several states and directed officials to accelerate on-ground execution, ensure timely completion and strengthen monsoon preparedness through drainage and slope protection measures.

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