Real Object Augmented Defect Detection.
R.O.A.D.D turns raw drone orthomosaic and LiDAR captures into classified road geometry, defect inventories, and CAD/GIS-ready exports — turning weeks of manual annotation into a same-day pipeline.
Built by Imataka Tech · 100% Guyanese
Drones have made capturing road corridors fast and cheap — flights that once took field crews days now take hours. But the pipeline after the flight hasn't caught up: raw orthomosaic and LiDAR captures still go through manual annotation before anyone can act on them.
Drone corridors get flown in minutes, but the orthomosaic and LiDAR they produce are still reviewed road by road, on foot, by hand — turning a fast capture into a slow bottleneck.
Defects get logged, but they're rarely ranked against budget, risk, or urgency — leaving engineers to guess which repair matters most.
Nothing links a detected defect to a maintenance action. Data sits in a report while the road keeps deteriorating underneath it.
R.O.A.D.D ingests drone-captured orthomosaic and LiDAR data, then runs it through a processing pipeline that segments, classifies, and measures — so the output is ready for engineers, not just a picture of the road.
Road centerlines, carriageway edges, and shoulders are segmented directly from orthomosaic and LiDAR data, alongside urban features like buildings, vegetation, and drainage — each with geometric and area attributes attached.
Surface defects — cracking, ravelling, potholes, patching — are detected from imagery, while rutting, depressions, and joint faulting are picked up from LiDAR. Every defect is classified by type and severity, and geolocated.
Classified output is converted into clean vector geometry with attribute tables, then exported directly into QGIS, AutoCAD, and Civil 3D — ready for the workflows engineering teams already use.
Drone orthomosaic + LiDAR uploaded into a project
Road features & defects segmented and classified
Geometry generated, severity scored
Inspect, correct, or override in the web viewer
Geometry & reports pushed to QGIS, AutoCAD, Civil 3D
Technical teams that capture or procure drone orthomosaic and LiDAR data for road and land development projects. R.O.A.D.D turns raw captures into classified features, defect inventories, and CAD/GIS-ready geometry — without weeks of manual annotation.
Teams managing road networks and land use decisions. R.O.A.D.D delivers land use reports, road feature summaries, and a geolocated defect inventory that can be ranked against budget and risk.
R.O.A.D.D turns drone captures into CAD and GIS-ready road intelligence. Get in touch to learn more.