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NEREUS: A Space-Based Maritime Surveillance System for Fisheries Monitoring and Anomaly Detection

The NEREUS project, led by the Surrey Space Centre (SSC) in collaboration with the Mauritius Research and Innovation Council (MRIC), aims at developing a tool, based on a Machine Learning algorithm to detect anomalies in maritime satellite data. Analysing these anomalies is very important in ensuring maritime security and environmental protection. The key application for this tool is the detection of potential Illegal, Unreported and Unregulated (IUU) fishing activities, to improve sustainable management of marine resources. The novelty of the NEREUS machine learning algorithm is that it maximises data fusion potential between various satellite technologies. Detection is performed using maritime satellite data mainly from Synthetic Aperture Radar (SAR) and self-reporting data like the Automatic Identification System (AIS) data. Furthermore, the system can also use the Vessel Monitoring system (VMS) for vessel tracking, and ancillary data to add contextual information to the analyses. Examples of the outputs of the monitoring tool will be products identifying areas where ships frequently do not report their presence over some period of time. This information can be used by authorities to make informed decisions and contribute towards effective Maritime Domain Awareness. Thus, the products can support the detection of IUU fishing activities with obvious environmental, economic and societal benefits for local communities. Therefore, by the end of the NEREUS project it would be of the utmost importance to have Mauritian stakeholders trained to the use the tool so that the benefits can continue beyond the duration of the project. This online training covers the following: 1. Basics of Anomaly Detection 2. Introduction to the NEREUS tool 3. The NEREUS workflow: Ship trajectory prediction Heatmap generation Enhanced Maritime Situational Picture 4. Innovation and value added by the tool