POSEIDON

Earth Observation and Artificial Intelligence for Maritime Pollution Detection, Monitoring and Compliance 

The marine ecosystems are constantly being added with more pressure, as the globally increasing maritime traffic results in increased pollution from oil spills, vessel emissions, sewage and litter. Illegal fishing, discharges and waste dumping activities, enhance the need to develop and use innovative tools and methods for detecting, characterising and attributing to their source such environmental offences.  

The Horizon Europe POSEIDON project, Pollution Observation from Space: Environmental Imaging for Detections in the Oceans & Nearshore, is funded by the European Union and comprises ten partners from Europe, Canada and Asia, in order to exploit the recent advances in Earth Observation and Artificial Intelligence, and creates solutions for supporting and strengthening the implementation of the MARPOL regulatory framework, the Ship Sourced Pollution Directive and the European Union Environmental Crime Directive.

“The project intends to leverage optical and radar-based satellite technology for improving services for identifying oil spills, detecting oil spills in sea ice conditions, and detecting and identifying chemicals, sewage, garbage, emissions, and other pollutants released by ships at sea.”

How?

The services for identifying and detecting oil spills and chemicals in the oceans, sewage, garbage, gas emissions and other pollutants released by ships at sea, including sea ice conditions, are improved by leveraging and integrating various technologies, such as multi-sensor satellites, vessel tracking information, in-situ measurements, environmental models and AI-based analytics. 

The five international test sites that have been selected, Elefsis Gulf in Greece, Strait of Gibraltar, Maldives, Singapore Strait and Arctic regions, demonstrate these capabilities as they not only face unique and complex environmental conditions, but they also address various challenges that may have societal and economic impact if not identified and tackled in time. 

POSEIDON showcases how the utilisation of different data sources can be incorporated into operational workflows to strengthen the prompt environmental crime detection and improve the situational awareness. Moreover, it identifies technical, operational, and institutional challenges and supports developing a stronger collaboration between enforcement authorities and the scientific community, aiming to contribute to the wider uptake in decision-making. 

Work packages

POSEIDON Project Timeline

POSEIDON project timeline

36 months — from kickoff in June 2026 to final demonstration
YEAR 1 YEAR 2 YEAR 3 Phase 1 Scoping & KPIs Phase 2 AI Development & QA Phase 3 Demonstration & Validation Kickoff M1 Baseline established KPIs & data plan · M6 AI prototypes ready M18 Prototypes validated M30 Project completion M36

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