Automatic Fusion of Satellite Imagery and AIS data for Vessel Detection

Milios, Aristides; Bereta, Konstantina; Chatzikokolakis, Konstantinos; Zissis, Dimitris; Matwin, Stan

doi:10.23919/fusion43075.2019.9011339

Cited by 11 publications

(4 citation statements)

References 18 publications

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“…there is a possibility that these systems can be shut down and/or modified in illegal activities [78]. The result (Table 5) is understandable when the VMS is considered alone as a maritime surveillance system data source.…”

Section: Maritime Surveillance System Model Proposal and Scenariosmentioning

confidence: 97%

“…The main reason for this situation is that this study mainly focuses on threats such as sabotage, terrorism, smuggling, illegal fishing, etc. Although suspicious contact is subject to VMS legislation, there is a possibility that these systems can be shut down and/or modified in illegal activities [78]. The result (Table 5) is understandable when the VMS is considered alone as a maritime surveillance system data source.…”

Section: Evaluation Of Alternativesmentioning

confidence: 99%

See 1 more Smart Citation

Safety–Security Analysis of Maritime Surveillance Systems in Critical Marine Areas

Şengül,

Yılmaz,

Uğurlu

2023

Sustainability

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In today’s world, wherein more than 80% of world trade is carried out by maritime routes, the safety and security of the seas where this trade takes place is of vast importance for nations and the international community. For this reason, ensuring the sustainable safety and security of the seas has become an integral part of the mission of all maritime-related entities. Using big data extracted from the seas and maritime activities into meaningful information with artificial intelligence applications and developing applications that can be used in maritime surveillance will be of great importance for augmenting maritime safety and security. In this article, data sources which can be used by a maritime surveillance system based on big data and artificial intelligence technologies and which can be established around sensitive sea areas and critical coastal facilities, are identified and a model proposal using this maritime big data is put forward.

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Section: Maritime Surveillance System Model Proposal and Scenariosmentioning

confidence: 97%

Section: Evaluation Of Alternativesmentioning

confidence: 99%

Safety–Security Analysis of Maritime Surveillance Systems in Critical Marine Areas

Şengül,

Yılmaz,

Uğurlu

2023

Sustainability

View full text Add to dashboard Cite

show abstract

“…In [ 9 ], Side-Looking Airborne Radar (SLAR) images were used as input to a two-stage CNN to detect ships and oil spills. In [ 10 ], a multi-stage data-centric workflow integrating optical satellite imagery and AIS data for automatic vessel detection is presented. This hybrid approach resulted in real world accuracy of 86–90%.…”

Section: Introductionmentioning

confidence: 99%

Every Vessel Counts: Neural Network Based Maritime Traffic Counting System

Petković,

Vujović,

Kaštelan

et al. 2023

Sensors

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Monitoring and counting maritime traffic is important for efficient port operations and comprehensive maritime research. However, conventional systems such as the Automatic Identification System (AIS) and Vessel Traffic Services (VTS) often do not provide comprehensive data, especially for the diverse maritime traffic in Mediterranean ports. The paper proposes a real-time vessel counting system using land-based cameras is proposed for maritime traffic monitoring in ports, such as the Port of Split, Croatia. The system consists of a YOLOv4 Convolutional Neural Network (NN), trained and validated on the new SPSCD dataset, that classifies the vessels into 12 categories. Further, the Kalman tracker with Hungarian Assignment (HA) algorithm is used as a multi-target tracker. A stability assessment is proposed to complement the tracking algorithm to reduce false positives by unwanted objects (non-vessels). The evaluation results show that the system has an average counting accuracy of 97.76% and an average processing speed of 31.78 frames per second, highlighting its speed, robustness, and effectiveness. In addition, the proposed system captured 386% more maritime traffic data than conventional AIS systems, highlighting its immense potential for supporting comprehensive maritime research.

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“…Stakeholders, such as authorities and investors, need to analyze these data in an interactive, online fashion for timely market surveillance or investment risk/opportunity identification purposes. In maritime surveillance applications, one needs to fuse high-velocity position data streams of hundreds of thousands of vessels across the globe and satellite, aerial images [2] of various resolutions. In all these scenarios, data volumes and rates are only expected to rise in the near future.…”

Section: Introductionmentioning

confidence: 99%