A Multi-Faceted Approach to Maritime Security: Federated Learning, Computer Vision, and IoT in Edge Computing

Mateus R Cruz, Eduardo Henrique Teixeira, Samuel Mafra, Felipe Augusto Pereira de Figueiredo

DOI: 10.14209/sbrt.2023.1570923804

Evento: XLI Simpósio Brasileiro de Telecomunicações e Processamento de Sinais (SBrT2023)

Keywords:

Abstract

Brazil faces several challenges related to maritime monitoring, including illegal fishing, drug trafficking, oil spills, and other environmental hazards. Recent advances in Computer Vision and artificial intelligence (AI) offer new possibilities for improving the efficiency and effectiveness of maritime monitoring systems. This paper proposes a multi-faceted approach that combines federated learning, computer vision, and IoT in edge computing to automate the detection and analysis of maritime activity. The proposed approach can enable faster and more accurate decision-making for improved maritime security.

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