The Search and Rescue (SaR) Use Case will demonstrate the potential of AI4COPSEC heterogeneous multi-sources data and technological bricks for supporting coordinated efforts across various Search and Rescue (SaR) entities in respect with the EU policy. The Use Case refers to the IAMSAR Manual which is designed to enhance the effectiveness and efficiency of SaR operations. By optimising search patterns detection and strategies to improve the likelihood of successful rescues, this Use Case will show that SaR operations can be conducted swiftly and effectively in the context of CSS enhancement. Drift analysis and the use of reliable total ocean surface currents are crucial in SaR operations as they significantly impact the search area’s determination.
By understanding the movement of water, rescuers can more accurately predict the drift of objects or persons in distress, leading to more focused and efficient search efforts. This approach not only saves valuable time but also resources, enhancing the likelihood of a successful rescue.
Operational Scenario for Search and Rescue
In this real-time UC, several AI4COPSEC results are used, namely fused real time surface currents, Melodi drifters, OSINT data, drift model relying on recurrent neural networks and open-source drift models such as GNOME or OpenDrift. The open-source drift models’ accuracy will be enhanced with live weather and ocean data, incorporating multiple ocean current products. The performance will be evaluated through indicators like the normalised cumulative Lagrangian separation (NCLS) and applied in a live SaR operation to optimise the search grid and reduce response time.
