Eye in the sky: condition monitoring of transportation infrastructure using drones

Abstract

A study was undertaken into using unmanned aerial vehicles or drones to inspect the condition of a range of transport infrastructure. A road intersection, bridge and railway crossing in the USA were each inspected using two different types of drone. Machine-learning-based feature-identification techniques, developed in an earlier case study of a car parking lot, were then used to extract information automatically from the remotely captured photogrammetric data for each asset. The findings and analysis results will help to optimise future transportation infrastructure health monitoring using unmanned aerial vehicles.