Bengaluru: East Civic Body Uses AI to Identify Potholes Across 1,600 km of Roads

Bengaluru's East civic body has completed an AI-powered survey of nearly 1,600 km of roads using specialised cameras and the YOLO model. The technology detects potholes, measures road damage, and helps officials accurately estimate materials and costs for road repairs.

The Bruhat Bengaluru Mahanagara Palike (BBMP) has completed an Artificial Intelligence (AI)-based survey of nearly 1,600 kilometres of roads in Bengaluru's East Zone, marking a significant step towards data-driven road maintenance. East Zone Commissioner DS Ramesh said the survey was conducted using vehicles equipped with specialised cameras and the YOLO (You Only Look Once) image processing model. The AI-powered assessment has generated detailed data on road conditions, enabling officials to plan repair works with greater accuracy and efficiency.

Survey Identifies Potholes and Road Damage

Speaking at a meeting with officials on Wednesday, Ramesh said the survey has provided precise information on the condition of roads across the East Zone. The AI system identified the number of potholes, the extent of surface damage, and locations where roads had been dug up for utility works, providing a comprehensive assessment of the road network.

AI Calculates Exact Pothole Dimensions

Ramesh said the technology uses a Vision Language Model to measure the exact length and width of every pothole. For instance, the AI report found that Vibhutipura ward alone requires nearly 144 square metres of road patchwork.

Accurate Data to Improve Road Repairs

According to Ramesh, the AI-generated data will help the civic body accurately estimate the quantity of hot mix, construction materials, and funds required for road repairs before work begins. He added that this data-driven approach would improve planning and resource allocation for road maintenance across the East Zone, except for road development projects that have already been approved under separate government grants.