Innovative, non-invasive environmental monitoring technology tested at German windfarm

Among technologies used, the project saw a drone equipped with a high-resolution camera used for offshore monitoring. Using the technique reduces CO2 emissions and is a less intrusive alternative to traditional methods of observing birds and marine mammals, which are based on aircraft and ships.

The drone is just one of a number of monitoring technologies being deployed as part of RWE’s SeaMe (Sustainable ecosystem approach in Monitoring the marine environment) project. The goal of the project is to develop a holistic understanding of the interactions between offshore windfarms and the ecosystem.

Alongside the drone, an AI-powered fish detection system with video cameras is being operated on an autonomous underwater vehicle. High-resolution video cameras have also been installed on turbines, to monitor birds and their behaviour, and water samples are being analysed for traces of environmental DNA.

The project began in autumn 2024, initially with onshore testing and preparation of the various technologies for offshore deployment. It has now entered its next phase, starting simultaneous data collection at the Kaskasi windfarm.

The long-range drone, a Primoco UAV One 150 operated by BioConsult SH, can remain airborne for up to 15 hours. It is fitted with an optimised HiDef video system for autonomous operation, ensuring consistency with historical data as the camera provides the same coverage and resolution as conventional aerial surveys. During its initial test, the drone flew approximately 500 m above the offshore windfarm, neighbouring windfarms and a reference area at sea. Recorded footage will be analysed in the coming weeks using artificial intelligence and human quality control.

RWE says the technology provides a less intrusive and low-emission way to monitor birds and marine mammals – such as porpoises - removing the need for human observers at sea or the use of aircraft. According to BioConsult SH, using the drone can reduce the carbon footprint of monitoring by up to 90 percent.

Six high-resolution video cameras were installed on two wind turbines to track birds and their behaviour around the clock. Spoor’s AI-based analysis allows for automatic evaluation, accurate detection, tracking, and identification of birds. Technologies for night-time monitoring, such as infrared illumination and a thermal imaging camera, are also being tested. The details that can be captured in this way complement and advance traditional bird monitoring approaches such as radar and provide greater coverage than approaches such as aerial photography. Thanks to high-resolution images and expert validation by ornithologists, birds can be accurately identified even from great distances, providing valuable insights into site- and species-specific behaviour.

Continuous monitoring is also being carried out underwater and underwater camera systems have been installed to operate day and night. In contrast to conventional methods that are invasive and conducted only once a year, the system developed in collaboration with Danish start-up Anemo Robotics enables fully autonomous, non-invasive monitoring of marine fauna. Cameras capture 30-second clips every 15 minutes over several months, generating a comprehensive data set that is AI-analysed, making both short-term behaviours and long-term ecological trends visible.

Functionality and logistics used to deploy and retrieve an autonomous underwater vehicle have also been successfully tested, for the first time. The vehicle was launched and recovered by a vessel that is usually used for windfarm maintenance. Developed by the Robotics Innovation Centre at the German Research Centre for Artificial Intelligence, the underwater vehicle is equipped with cameras, sonars, and oceanographic sensors to identify fish, marine mammals, and benthic animals, while simultaneously recording oceanographic parameters.

The project takes a holistic view of the marine ecosystem by simultaneously recording both physical and biological parameters, including aspects often overlooked in traditional monitoring programs. This includes phytoplankton (microscopic algae) and zooplankton (such as small animals), which play crucial roles in the food chain. Additionally, physical parameters such as temperature, salinity, and oxygen levels are measured to explain changes in species distribution and abundance. These parameters are collected using the autonomous underwater vehicle.

Water samples are analysed for environmental DNA or ‘eDNA’ to determine which species are present in the area. Unlike conventional methods that involve collecting and removing animals from the sea, the SeaMe team focuses on the genetic traces left behind, such as faeces, skin cells, mucus, or other cellular residues shed into seawater. Comparing DNA sequences with a database of known species enables scientists at the Helmholtz Institute for Functional Marine Biodiversity (HIFMB) and the Alfred Wegener Institute (AWI) to identify the originating species without collecting the animals. Initial analyses of samples taken near Heligoland have identified 143 different species, from phytoplankton and zooplankton, to worms, crabs, fish, and marine mammals, including the harbour porpoise native to the German North Sea.