TII revolutionises national road condition monitoring
Transport Infrastructure Ireland has introduced an AI-driven system that enhances how road surface conditions are recorded and analysed. This innovation improves safety and maintenance efficiency across Ireland’s national roads and active travel routes.
Source:
TII & Luas Infrastructure News
•
⏱️ 1 min read
Transport Infrastructure Ireland (TII) has launched a pioneering approach to monitoring the condition of the National Road Network (NRN) and active travel infrastructure. By leveraging data-driven, AI-enabled asset intelligence, TII has transformed how road pavement conditions are collected, assessed, and managed, benefiting asset managers, engineers, and road users alike.
Previously, TII relied on periodic machine surveys and manual inspections conducted over multi-year intervals, which limited timely defect detection and hindered continuous monitoring. The new system integrates five core elements: smartphone and camera-based data collection methods to expand coverage cost-effectively; AI and computer vision analytics to automatically identify and classify defects; consolidation of multiple data sources including traditional surveys and LiDAR; cloud-based GIS platforms for data visualisation; and connected vehicle data providing near real-time road roughness information.
This comprehensive solution offers near real-time access to standardised condition scores and defect visualisations, enabling improved lifecycle planning and investment decisions. It marks a shift from episodic inspections to continuous, predictive asset management, enhancing network-wide visibility and operational efficiency. The project has been recognised as a finalist in the Infrastructure, Assets & Built Environment Digitisation category at the Ireland eGovernment Awards.
Previously, TII relied on periodic machine surveys and manual inspections conducted over multi-year intervals, which limited timely defect detection and hindered continuous monitoring. The new system integrates five core elements: smartphone and camera-based data collection methods to expand coverage cost-effectively; AI and computer vision analytics to automatically identify and classify defects; consolidation of multiple data sources including traditional surveys and LiDAR; cloud-based GIS platforms for data visualisation; and connected vehicle data providing near real-time road roughness information.
This comprehensive solution offers near real-time access to standardised condition scores and defect visualisations, enabling improved lifecycle planning and investment decisions. It marks a shift from episodic inspections to continuous, predictive asset management, enhancing network-wide visibility and operational efficiency. The project has been recognised as a finalist in the Infrastructure, Assets & Built Environment Digitisation category at the Ireland eGovernment Awards.
0 views