NHAI Uses In-House AI To Flag Highway Project Issues
ROADS & HIGHWAYS

NHAI Uses In-House AI To Flag Highway Project Issues

The National Highways Authority of India (NHAI) has deployed an in-house artificial intelligence (AI) system to detect discrepancies in detailed project reports (DPRs), verify site conditions and flag issues before they cause delays or cost overruns. The Technical Schedule Analyzer compares DPR data with technical standards, policy provisions and a repository of field data to identify inconsistencies in planning.

NHAI said the Analyzer currently examines Schedule B and Schedule C sections to check quantities and specifications against Indian Roads Congress codes, Ministry of Road Transport and Highways norms and NHAI standards. The authority indicated the tool aims to reduce planning omissions that can produce large cost variations, noting that in a Rs 20 billion (Rs 20 bn) project variations of about Rs 2 bn to Rs 3 bn may arise.

Officials said the system will draw data from drone surveys, network survey vehicle records, geospatial information, monthly progress reports and site photographs to verify whether plans match ground conditions. It is part of an AI ecosystem built by the authority's AI Cell and complements Margsarthi, the in-house AI assistant trained on circulars, Acts, codes and approved technical documents.

Margsarthi, launched in April, has handled more than 50,000 queries from around 1,100 users across the organisation, with each response linked to source documents so officers can verify recommendations. Access is already available to officers nationwide and is planned to be extended to authority and independent engineers associated with projects.

Officials said the applications are intended to assist rather than replace decision-making and that accountability for project decisions will remain with officers. The authority described a multidisciplinary effort involving civil and AI engineers and design specialists to digitise manuals and standards into a structured repository. Work under development includes automated defect analysis, maintenance planning and AI-assisted drawing reviews.

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The National Highways Authority of India (NHAI) has deployed an in-house artificial intelligence (AI) system to detect discrepancies in detailed project reports (DPRs), verify site conditions and flag issues before they cause delays or cost overruns. The Technical Schedule Analyzer compares DPR data with technical standards, policy provisions and a repository of field data to identify inconsistencies in planning. NHAI said the Analyzer currently examines Schedule B and Schedule C sections to check quantities and specifications against Indian Roads Congress codes, Ministry of Road Transport and Highways norms and NHAI standards. The authority indicated the tool aims to reduce planning omissions that can produce large cost variations, noting that in a Rs 20 billion (Rs 20 bn) project variations of about Rs 2 bn to Rs 3 bn may arise. Officials said the system will draw data from drone surveys, network survey vehicle records, geospatial information, monthly progress reports and site photographs to verify whether plans match ground conditions. It is part of an AI ecosystem built by the authority's AI Cell and complements Margsarthi, the in-house AI assistant trained on circulars, Acts, codes and approved technical documents. Margsarthi, launched in April, has handled more than 50,000 queries from around 1,100 users across the organisation, with each response linked to source documents so officers can verify recommendations. Access is already available to officers nationwide and is planned to be extended to authority and independent engineers associated with projects. Officials said the applications are intended to assist rather than replace decision-making and that accountability for project decisions will remain with officers. The authority described a multidisciplinary effort involving civil and AI engineers and design specialists to digitise manuals and standards into a structured repository. Work under development includes automated defect analysis, maintenance planning and AI-assisted drawing reviews.

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