Fusion of Ground-Based and UAV Data for Rail Infrastructure Monitoring – a conceptual example at the Port of Brunswick (Braunschweig, Germany)

Abstract

The integrity of railway tracks and their immediate surroundings is crucial for safe and efficient rail operation. Current practices of inspection especially for branch lines and industrial networks heavily rely on regular visual inspections by foot, supported by trolly-based measurements at long time intervals. This is labor-intensive, safety-critical and time-consuming. And in far most cases, it is not sufficient to introduce schemes of predictive maintenance for proactively identifying and solve potential issues. This study presents a concept to investigate the integration of in-service ground-based/terrestrial and unmanned aerial vehicle (UAV)-based monitoring systems to enhance inspection of railway track and surrounding areas. By combining data from embedded terrestrial sensors with UAV-mounted sensors such as RGB cameras and LiDAR, we aim to develop a comprehensive monitoring system capable of detecting track anomalies, vegetation encroachment and infrastructure degradation with greater accuracy and efficiency. The potential benefits include reduced inspection and maintenance costs, improved safety, comprehensive monitoring of peripheral areas, minimized service disruptions, increased objectivity and a shift towards predictive maintenance strategies, especially for smaller railway infrastructure operators.