NHAI To Use 40,000 AI Dashcams To Find Potholes On Highways
The National Highways Authority of India has announced a massive technological upgrade to streamline the maintenance of its sprawling road network. The highway authority will deploy advanced artificial intelligence dashcams across approximately 40,000 kilometres of national highways. This new monitoring initiative is designed to drastically reduce the time it takes to identify and repair critical road hazards, primarily focusing on dangerous potholes and deteriorating pavement conditions.
Image courtesy Cyberswift
Currently, identifying broken road surfaces relies heavily on manual inspections and delayed physical reports from patrol teams or commuters. The new system removes this manual bottleneck. Under the initiative, the highway authority will install specialized, high-resolution dashboard cameras directly onto its existing fleet of route patrol vehicles. These dedicated patrol vehicles will physically drive through their assigned highway stretches and conduct comprehensive surveys every single week.
As the patrol vehicles drive at standard highway speeds, the dashcams will continuously record the road surface. The integrated artificial intelligence software is trained to instantly recognize various types of pavement distress. The system will automatically detect and log the exact GPS coordinates of deep potholes, surface cracks, and general tarmac degradation. This real-time data will allow maintenance crews to pinpoint the exact location of a hazard without relying on vague manual descriptions.
While finding and fixing potholes remains the primary objective, the artificial intelligence software has been programmed to flag several other critical safety hazards. The camera system will actively monitor the condition of essential road infrastructure, including faded lane markings and damaged metal crash barriers. It will also record the presence of non-functional streetlights, which pose a severe risk during night time driving.
The system is designed to identify man-made safety violations. The software will instantly flag illegal openings cut into median dividers by locals, unauthorized commercial signboards blocking the line of sight, and vehicles parked illegally on highway shoulders. To ensure comprehensive safety, the highway authority has mandated that at least one of these automated surveys must be conducted entirely at night every month. This specific night time patrol will evaluate the visibility and performance of reflective road markings and highway signages under dark conditions.
The sheer volume of data generated by weekly surveys across 40,000 kilometres requires a robust backend infrastructure. The highway authority will track secondary maintenance issues as well, such as severe waterlogging during the monsoons, missing cast iron drainage covers, unchecked vegetation growth obstructing signs, and the physical condition of designated bus bays.
To manage this massive influx of information efficiently, the highway network has been divided into five distinct operational zones. All the data collected by the patrol vehicles will be fed into a centralized digital platform. This dedicated platform will analyse the reports, track the deteriorating road conditions over specific timelines, and automatically generate actionable repair dockets.
By utilizing artificial intelligence, the highway authority aims to move away from a reactive repair model toward a highly proactive maintenance strategy. The automated system will force regional contractors to fix problems much faster, significantly improving the safety and ride quality for regular highway commuters.