Leveraging predictive maintenance
Road inspections are labor intensive and a time consuming task and automating visual road inspections are notoriously difficult because of the amount of types of damages, variety in pavement surfaces and the likelihood that damage can occur everywhere.
BrainMatter learns to recognise 12 segments of road surface conditions based on the guidelines of CROW or Rijkswaterstaat in days versus weeks.
BrainMatter users can define rules to initiate follow-up actions when a damage has been recognized, such as a notification or signal to an asset management system, like IBM Maximo, such a road maintenance work order can be initiated
Download the case study and find out how BrainMatter's intelligent automation powers Unihorn’s solution, ‘Inspech’, which aims to detect damage to roads using camera images taken by a specifically designed car equipped with a camera set-up for visual road inspection.
Inspech also uses proprietary algorithms that automatically classify road surface segments in accordance with the guidelines of the CROW or Rijkswaterstaat.