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Punjab Government Saves Rs 383 Crore in Road Repairs with AI-Powered Survey

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Chandigarh: The Punjab government has reported massive savings of Rs 383.53 crore by using Artificial Intelligence (AI) to assess the condition of link roads, preventing unnecessary repairs on stretches that were still in good shape.

According to the latest survey, conducted across 843 link roads in 23 districts, repair proposals were initially prepared for over 1,355 km of roads that, in reality, required no urgent maintenance. Officials revealed that in many cases, where road conditions were shown to have large potholes, the AI assessment found only minor or no damage at all.

Punjab Mandi Board officials explained that the AI survey was carried out in two stages. Vehicles fitted with drone cameras and road sensors conducted 360-degree videography, while AI systems analyzed cracks, potholes, and surface wear. The technology generated digital reports with GPS coordinates, ensuring precise identification of sections truly in need of repair.

“By relying on AI-based road inspection, the state avoided unnecessary expenses and ensured transparency in the repair process,” said party spokesperson Neel Garg, adding that the government is committed to protecting public funds while delivering timely infrastructure upgrades.

This is not the first time AI has helped Punjab save money. In 2022-23, a pilot project in two districts cost the government just Rs 4.5 lakh but helped save Rs 60 crore in road repair costs. Later, during the preparation of the 2025–26 repair plan, the use of AI in combination with videography and physical verification further boosted savings from an earlier figure of Rs 121.39 crore to the current Rs 383.53 crore.

Officials admitted that in the past, some repair proposals included link roads that were still in good condition, often added due to local political pressure. With AI surveillance now in place, such discrepancies are being eliminated.

The state government believes that beyond financial savings, the technology will help ensure timely, need-based repairs and build public confidence in infrastructure management.

All news on Encounter News is computer-generated and sourced from third parties. Please read and verify carefully. We will not be responsible for any issues. 

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