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• NHAI has introduced a predictive asset management framework to improve National Highway maintenance through technology-driven monitoring.
• Advanced tools such as survey vehicles, drones, AI-powered dashcams and pavement testing systems will be used to detect defects at an early stage.
• Data from various monitoring platforms will be integrated into a centralised system for real-time assessment of highway conditions.
• The initiative aims to enable timely repairs, improve road quality, extend asset life and enhance commuter experience.
The National Highways Authority of India (NHAI) has launched a predictive asset management framework for the operation and maintenance of National Highways, marking a significant shift from traditional maintenance practices towards a technology-driven and data-based approach.
The initiative is aimed at ensuring that highway assets remain in optimal condition through early identification of deterioration and timely corrective action. By adopting predictive maintenance methods, NHAI seeks to improve the quality, safety and longevity of the National Highway network while reducing the risk of major infrastructure failures.
The new framework is built around three key pillars. The first focuses on large-scale asset condition monitoring through advanced survey and inspection technologies. NHAI has deployed Network Survey Vehicles (NSVs) across operational highway stretches to collect data on pavement conditions, including roughness, rutting, cracking and structural distress.
In addition, Drone Analytics Monitoring Systems (DAMS) are being used to create digital inventories of highway assets, inspect structures and identify encroachments. Falling Weight Deflectometer (FWD) testing has also been introduced to assess pavement strength and detect weakening sections before visible damage appears. To further strengthen monitoring capabilities, NHAI has begun deploying AI-powered Dashcam Analytics Services (DAS), which can automatically identify issues such as potholes, damaged crash barriers, faulty lighting systems and drainage deficiencies.
The second pillar involves the development of a centralised asset intelligence ecosystem. Data generated from survey vehicles, drones, dashcams and pavement testing equipment is being integrated into a unified platform, providing a comprehensive view of asset conditions across the National Highway network. This approach is expected to replace fragmented inspection methods with a continuously updated digital record of infrastructure health.
The third pillar centres on predictive monitoring and risk-based decision-making. By analysing historical performance data alongside real-time monitoring inputs, NHAI will be able to identify vulnerable stretches, detect emerging trends and prioritise maintenance activities before issues become critical.
The framework is also supported by standardised maintenance procedures, improved contract management systems and performance-based monitoring mechanisms. These measures are intended to ensure that maintenance interventions are carried out efficiently and consistently across the network.
According to NHAI, the adoption of predictive asset management represents a major step towards modernising highway operations and maintenance. Through the integration of advanced monitoring technologies, artificial intelligence and data analytics, the authority aims to optimise maintenance expenditure, enhance infrastructure performance and provide a safer and more reliable travel experience for highway users across the country.
Source: PIB
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