The reliable monitoring of pipeline right-of-way areas is a key responsibility for network operators to ensure supply security, comply with regulations, and detect potential risks to infrastructure at an early stage. Traditional inspection methods relying on human observers are time-consuming, resource-intensive, and prone to human error. Moreover, they provide only a snapshot of the corridor at the time of inspection flights or patrols—leaving the operator effectively “blind” on all other days.

In a joint pilot project between the German network operator Westnetz and Beagle Systems, an innovative approach has been developed to significantly improve the efficiency and quality of right-of-way inspections. Beagle Systems, as the service provider, employs a combination of ultra-light aircraft and long-range unmanned aerial systems to capture high-resolution imagery, complemented by satellite data. The collected data are analyzed using AI-based algorithms to automatically detect unauthorized activities along the pipeline corridor, such as construction vehicles or material deposits.

The paper outlines the workflow—from data acquisition and automated analysis to the integration of results into existing operational and documentation processes. Emphasis is placed on the fusion of multiple data sources and the practical implementation within Westnetz’s operations. Initial results show that potential risks can be identified earlier and resources utilized more efficiently.

This approach enables network operators to optimize maintenance strategies through data-driven insights and to strengthen the sustainable protection of critical infrastructure.