We worked together to develop a smart solution based on Microsoft Azure, machine learning and AI that is used for training customised algorithms that can accurately detect and classify all kinds of road surface damage. The new solution improves the speed, quality, efficiency and accuracy of visual road surface inspections. In addition, it enables predictive asphalt maintenance and reduces costs by allowing inspectors to focus their expertise where it is really needed.
'Because our inspectors don’t have to watch the whole video, but only the images selected by the model, we now do the work that used to take days or weeks in a few hours' - Kitting Lee, Director Digital Asset Management at BAM Infra Nederland
Costly repairs & danger
Already on the very first day after a road has been paved, the surface begins to show signs of wear and tear due to the influence of weather and traffic loads. If not discovered in time, small cracks and scuffs and other damages will lead to major problems such as traffic disruption and other potentially dangerous situations.
To help prevent these situations on the road and make them less problematic, we partnered with BAM Infra Nederland, a subsidiary of Royal BAM Group (BAM), a European construction company that is operational worldwide. Together, we endeavour to increase efficiency and reduce costs by applying advanced imaging and analysis technology to the never-ending challenges of inspecting and maintaining highways, urban streets, car parks and other paved surfaces on which people walk and drive day in and day out.
Want to know more about this project?
Download the casestudy here
