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Federated Learning and Trajectory Compression for Enhanced AIS Coverage

2025-12-03 · Thomas Gräupl, Andreas Reisenbauer, Marcel Hecko, Anil Rasouli, Anita Graser, Melitta Dragaschnig, Axel Weissenfeld, Gilles Dejaegere, Mahmoud Sakr arxiv

This paper presents the VesselEdge system, which leverages federated learning and bandwidth-constrained trajectory compression to enhance maritime situational awareness by extending AIS coverage. VesselEdge transforms vessels into mobile sensors, enabling real-time anomaly detection and efficient data transmission over low-bandwidth connections. The system integrates the M3fed model for federated learning and the BWC-DR-A algorithm for trajectory compression, prioritizing anomalous data. Preliminary results demonstrate the effectiveness of VesselEdge in improving AIS coverage and situational awareness using historical data.

📄 PDF Abstract BibTeX arXiv:2512.03584

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Federated LearningAnomaly Detection

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