thesis
LiDAR Road Condition Monitor
Undergraduate thesis. LiDAR point cloud processing pipeline with YOLOv8 for automated road defect classification and monitoring.
- year
- 2024
- role
- Undergraduate thesis
- domain
- Research
- type
- ML
What it took
LiDAR point clouds processed into road surface rasters ready for detection.
YOLOv8 trained to classify defect types — cracking, ravelling, potholes.
Output exported as GIS layers so a maintenance team can act on it directly.
built with
LiDARYOLOv8Point CloudPythonGIS