ecoBay
ecoBay – AI-Driven Robotics and genetic monitoring for early detection of biodiversity change in Bavarian lakes
ecoBay combines genetic biodiversity monitoring with autonomous robotics: an autonomous surface robot (uncrewed surface vehicle, USV) enables high-resolution assessment of biodiversity and lake status. AI-enabled adaptive mission planning selects the most informative sampling and measurement locations.
Motivation
Freshwater ecosystems are under increasing pressure, and current monitoring often captures genetic diversity only to a limited extent. ecoBay addresses this gap with an integrated approach that combines Environmental DNA and Environmental RNA (eDNA/eRNA) with continuous limnological time series. The USV repeatedly visits sampling and measurement sites, collects samples across different areas of the lake, and provides parallel real-time/continuous measurement data. From genome and transcriptome data, we derive species profiles, functional activity, and genetic indicators of lake health, and link them with water-quality data to build predictive models. ecoBay is tested in two model lakes: Ammersee and Großer Ostersee.
ecoBay tackles the challenge of taking measurements at the right place and the right time—where they are most informative. The platform combines robotic navigation and sensor data with an AI-enabled, information-driven selection of measurement locations. This makes sampling more efficient and spatially adaptive. In parallel, ecoBay couples genetic analytics (eDNA/eRNA) with physico-chemical sensing (e.g., temperature, oxygen, pH, nutrients) and validates the autonomous results against reference and manual data.
Research Topics
At the Munich Institute of Robotics and Machine Intelligence (MIRMI), the project team develops the robotic platform and the AI methods for field deployment. This includes autonomous data collection with an autonomous surface robot (uncrewed surface vehicle, USV), building on Environmental Sample Processor (ESP) concepts and integrating them into the platform, as well as data-driven control and planning methods for adaptive missions.
Links
ITR Team Members
- Stefan Sosnowski (principal investigator)
- tbd.