Recognition of situations and detection of anomalies

Short description

When data volumes are particularly high, decision-makers may overlook conspicuous or even safety-critical situations. As a support, methods can be used which automatically analyze spatio-temporal data sets in order to point out specific or conspicuous situations to the decision maker.

Such procedures are part of the field of artificial intelligence. On the one hand, specific situations can be described using expert knowledge and the resulting situation model can be used for pattern recognition. On the other hand, machine learning methods can be used to generate models that represent normal motion behavior. These can be used to detect anomalies.

Fields of application

One area of application is the maritime domain, where decision-makers monitor current maritime traffic. Possible methods for situation awareness and anomaly detection are addressed in the EU projects MARISA and OCEAN2020.



The EU-funded research project MARISA is about relieving and supporting people in maritime situation analysis in order to ensure the safety requirements and environmental protection that apply there.



This research project with 42 partners from 15 EU countries supports different areas in maritime surveillance. Fraunhofer IOSB is contributing its expertise in the field of underwater drones and maritime situation analysis.


Department IAD of Fraunhofer IOSB

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