Maintaining vast swathes of geographically dispersed roadside infrastructure, such as road signs and lamp-posts, is a significant cost for those responsible for its upkeep.
It’s costly and time consuming to send engineers to sites, especially if they can’t find what they’re looking for when they arrive. However, a newly developed AI and geotagging technology from geospatial company AI Mapit, which can pinpoint assets to within two metres, could revolutionise how this roadside infrastructure is managed.
“We’re using computer vision and artificial intelligence to create ‘digital twins’ of large networks of widely spread assets such as utility poles,” says chief executive Julie Connelly. “Trying to do this using traditional methods would be prohibitively expensive. AI is the only way to go. For example, Ireland has around 95,000km of roads, which we could add in a couple of weeks. This would take months by hand or site visits.”
AI Mapit uses TomTom maps as the basis for its inventories, which are highly detailed and include information about asset height and distance from verges. This is relevant for the type of machinery that might be needed to fix it. When an asset is identified and verified it is tagged with unique GPS co-ordinates.
The system then monitors the asset for wear and tear and visibility. This predictive capability makes maintenance more cost effective and streamlined for AI Mapit’s potential customers, which will include local authorities, large telecoms providers and big utility companies.
AI Mapit is an Irish Times Innovation awards finalist in the New Frontiers category sponsored by UCD Michael Smurfit Graduate Business School
