IIMEO aims to develop solutions for the automated monitoring of critical infrastructures. These will be built around two key requirements:

• The time between starting a monitoring task and receiving the results should be no more than one hour.
• Monitoring should be possible at any time of day and in all weather conditions.

To meet these goals, we designed the IIMEO system, which consists of three complementary parts: the on-board platform, the on-ground platform, and the user services.

The on-board platform refers to the component responsible for the data acquisition and intial processing. In the operational system, this would consist of small satellites in low Earth orbit; in the demonstration system, it is an aircraft equipped for this purpose. The system is equipped with state-of-the-art sensors (SAR and high-resolution RGB cameras) which complement one another and provide clear, reliable images regardless of weather conditions or the time of day. A powerful on-board processor uses artificial intelligence to detect changes and anomalies in the monitored infrastructure already on-board.

The on-ground platform acts as counterpart to the on-board platform and integrates the functionality required to manage the individual monitoring tasks, to receive, store and process data from the on-board system, and to provide the interface to the user services. It has a modular and scalable design and is operated within a cloud infrastructure.

The user services represent the main interface to the end-user for commanding the monitoring tasks and inspecting the corresponding results. The services can be accessed via a web browser or a mobile app.

Our Technologies

Infrastructure Monitoring – Pilot Case

Reliable transport infrastructure is crucial for a strong economy, providing access to markets, jobs, and social services. The two main types of land transport are roads and railways, with railways generally being safer. However, numerous accidents occur each year due to derailments and collisions with obstacles on or near the railway tracks. For this reason, the monitoring of railway tracks was selected as a pilot use case for the IIMEO project.

Among the most common obstacles are unauthorised access to the track and maintenance equipment left on the tracks. Other obstacles result from geological and natural hazards such as landslides, flooding and extreme weather conditions. Derailments can also be caused by track deformation resulting from earthquakes or extreme heat.

In recent decades, significant efforts have been made to develop systems for monitoring track conditions and detecting obstacles autonomously, improving safety and reducing the need for personnel to walk along the tracks. Only space-based approaches allow continuous monitoring of infrastructures on a large scale, while airborne solutions work well for small areas, but for larger areas the costs quickly outweigh the benefits. In addition, airborne solutions are also affected by weather conditions, making them unreliable during storms.

The route of the Küstenbahn Ostfriesland museum railway in northern Germany was selected for the pilot study; as the line was not in operation at the time of the campaign, it offered good opportunities to strategically place obstacles on the tracks to simulate potential disruptions. This setup enabled us to test how effectively the IIMEO system detects changes on the tracks caused by objects that are not part of the railway infrastructure.