Publications

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XX Publications
December 3, 2023
Big Data
Machine Learning
Navigating through dense waters: a toolbox for creating maritime density maps
Alexandros Troupiotis-Kapeliaris, Giannis Spiliopoulos, Marios Vodas, Dimitrios Zissis
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December 3, 2023
Big Data
Data Driven Digital Twins for the Maritime Domain
Alexandros Troupiotis-Kapeliaris, Nicolas Zygouras, Manolis Kaliorakis, Spiros Mouzakitis, Giannis Tsapelas, Alexander Artikis, Eva Chondrodima, Yannis Theodoridis, Dimitris Zissis
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December 4, 2023
Satellite Imagery
Vessel Traffic Density Maps Based on Vessel Detection in Satellite Imagery
Konstantina Bereta; Ioannis Karantaidis; Dimitris Zissis,
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December 4, 2023
Big Data
COVID-19 impact on global maritime mobility
Leonardo M. Millefiori, Paolo Braca, Dimitris Zissis, Giannis Spiliopoulos, Stefano Marano, Peter K. Willett & Sandro Carniel
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December 4, 2023
Machine Learning
A computer vision approach for trajectory classification
Ioannis Kontopoulos; Antonios Makris; Dimitris Zissis; Konstantinos Tserpes, 2021
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December 4, 2023
Big Data
A Big Data framework for Modelling and Simulating high-resolution hydrodynamic models in sea harbours
Spiliopoulos, K Bereta, D Zissis, C Memos, Ch Makris, A Metallinos, Th Karambas, M Chondros, M Emmanouilidou, A Papadimitriou, V Baltikas, Y Kontos, G Klonaris, Y Androulidakis, V Tsoukala
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December 4, 2023
No items found.
Modelling and simulating vessel emissions in real time based on terrestrial AIS data
Giannis Spiliopoulos, Dimitris Zissis, Julio de La Cueva, Ioannis Kontopoulos
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December 4, 2023
No items found.
Vessel detection using image processing and Neural Networks
Konstantina Bereta, Raffaele Grasso & Dimitris Zissis
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December 10, 2023
Big Data
MongoDB Vs PostgreSQL: A comparative study on performance aspects
Antonios Makris, Konstantinos Tserpes, Giannis Spiliopoulos, Dimitrios Zissis & Dimosthenis Anagnostopoulos
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December 10, 2023
Machine Learning
Big Data
A distributed framework for extracting maritime traffic patterns
Ioannis Kontopoulos, Iraklis Varlamis and Konstantinos Tserpes
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December 10, 2023
Artificial Intelligence
Satellite Imagery
Automatic Maritime Object Detection Using Satellite imagery
Konstantina Bereta, Raffaele Grasso & Dimitris Zissis
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December 10, 2023
Satellite Imagery
Vessel detection using image processing and Neural Networks
Konstantina Bereta, Raffaele Grasso & Dimitris Zissis
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December 10, 2023
Stream Processing
Real-time maritime anomaly detection: detecting intentional AIS switch-off
Ioannis Kontopoulos; Konstantinos Chatzikokolakis; Dimitris Zissis; Konstantinos Tserpes; Giannis Spiliopoulos
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December 10, 2023
Machine Learning
Stream Processing
Industry Paper: Classification of vessel activity in streaming data
Ioannis Kontopoulos, Konstantinos Chatzikokolakis, Konstantinos Tserpes, and Dimitris Zissis
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December 10, 2023
Data Fusion
Machine Learning
Automatic Fusion of Satellite Imagery and AIS data for Vessel Detection
A. Milios, K. Bereta, K. Chatzikokolakis, D. Zissis and S. Matwin
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December 10, 2023
Big Data
Machine Learning
A distributed spatial method for modeling maritime routes
D. Zissis, K. Chatzikokolakis, G. Spiliopoulos and M. Vodas
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December 10, 2023
Big Data
Machine Learning
A data driven approach to maritime anomaly detection
Zissis D. , Chatzikokolakis K. , Vodas M. , Spiliopoulos G. and Bereta K.
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December 10, 2023
Artificial Intelligence
Monitoring Marine Protected Areas using Data Fusion and AI Techniques
Konstantina Bereta, Aristides Millios, Konstantinos Chatzikokolakis, Dimitris Zissis
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December 10, 2023
Big Data
Machine Learning
Anomaly Detection white paper
Improving Maritime Situational Awareness Through Big Data Analytics, Machine Learning and Artificial Intelligence
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December 10, 2023
Big Data
Machine Learning
Stream Processing
A distributed lightning fast maritime anomaly detection service
K.Chatzikokolakis, D.Zissis,M.Vodas, G.Spiliopoulos,I.Kontopoulos
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December 15, 2023
Autonomous Vessels
Data Fusion
Preliminary Inter-comparison of AIS Data and Optimal Ship Tracks
Mannarini, Gianandrea; Carelli, Lorenzo; Zissis, Dimitris; Spiliopoulos, Giannis; Chatzikokolakis, Konstantinos
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December 15, 2023
Big Data
Machine Learning
A comparison of supervised learning schemes for the detection of search and rescue (SAR) vessel patterns
Konstantinos Chatzikokolakis, Dimitrios Zissis, Giannis Spiliopoulos,Konstantinos Tserpes
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December 15, 2023
Big Data
BigDataOcean Project: Early Anomaly Detection from Big Maritime Vessel Traffic Data
Konstantinos Chatzikokolakis, Dimitrios Zissis, Marios Vodas, Giannis Tsapelas, Spiros Mouzakitis, Panagiotis Kokkinakos, Dimitris Askounis,
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December 15, 2023
Machine Learning
Vessel Profile Indicators using Fuzzy Logic Reasoning and AIS
Konstantinos Chatzikokolakis, Dimitrios Zissis, Giannis Spiliopoulos
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December 15, 2023
Artificial Intelligence
Autonomous Vessels
Real Time Autonomous Maritime Navigation using Dynamic Visibility Graphs
Elias Xidias and Dimitris Zissis
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December 15, 2023
Big Data
Stream Processing
Countering Real-Time Stream Poisoning: An Architecture for Detecting Vessel Spoofing in Streams of AIS Data
Ioannis Kontopoulos, Giannis Spiliopoulos, Dimitrios Zissis, Konstantinos Chatzikokolakis, Alexander Artikis
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December 15, 2023
Big Data
Machine Learning
Mining Vessel Trajectory Data for Patterns of Search and Rescue
Konstantinos Chatzikokolakis, Dimitrios Zissis, Giannis Spiliopoulos and Konstantinos Tserpes
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January 10, 2024
No items found.
SELECT – Artificial Intelligence in Inland Navigation
FleetMon provided inland AIS data for the SELECT project of the TU Berlin. This article, published in the journal Internationales Verkehrswesen, features how data-based arrival time forecasts can increase the reliability of inland waterway transports.
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January 10, 2024
No items found.
CADMUSS – an innovative project to improve maritime safety
The evaluation of a (maritime) traffic situation requires sound training and professional experience. Decisions can be made based on this training and experience. (Partially) autonomous ships must be trained or require generalized algorithms to react appropriately in any situation. The goal is for vessels to be able to determine the technical manoeuvring distance and the required personal perceived safety distance.
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January 10, 2024
No items found.
Determining the bilge water waste risk and management in the Gulf of Antalya by the Monte Carlo method
FleetMon supported researchers at the Akdeniz University in Antalya, Turkey and their study on bilge water waste risk in the Gulf of Antalya.
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January 10, 2024
No items found.
FleetMon Supports the Development of Environmental Impact Assessment on the Brazilian Coast
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January 10, 2024
Emissions
Scrapping Probabilities and Committed CO2 Emissions of the International Ship Fleet
Abstract: Fighting climate change demands action in all sectors. International shipping faces the challenge of long lifetimes of vessels compared to other modes of transportation like cars or aircraft. Decisions on energy carriers and propulsion technologies that are made now have a long-lasting impact on the emissions of the sector.
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January 10, 2024
Emissions
The CO2 reduction potential of shore-side electricity in Europe
Abstract: Shore-side electricity can drastically reduce the emissions from fossil fuel-powered auxiliary engines of ships at berth. Data scarcity on the auxiliary power demand at berth has limited the scope and temporal resolution of previous studies to few ports and ships.
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January 10, 2024
Emissions
Estimation of worldwide ship emissions using AIS signals
The reduction of emissions is one of the main common goals all over the globe.
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January 10, 2024
Machine Learning
Routing Network
Scalable In-Database Machine Learning for the Prediction of Port-to-Port Routes
Authors: Dennis Marten, Carsten Hilgenfeld, Andreas Heuer
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January 10, 2024
Emissions
Green shipping: using AIS data to assess global emissions
Globalization and new environmental legislations lead to a rising need for new technological developments for the shipping industry
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January 10, 2024
Routing Network
How a real-time-based sea traffic forecast helps to organize and optimize the flow of maritime goods
As part of the PRESEA research project, which began in summer 2019, a real-time-based sea traffic forecast application is to be
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January 10, 2024
Routing Network
Generating a node in an AIS-based routing graph for improved Estimated Time of Arrival. (Big) Data challenge: using AIS for generating a routing graph
Abstract: For the international exchange of goods, an exact estimated time of arrival (ETA), especially in case of delays, is of great importance. Using global data of the automatic identification system (AIS) a grid node is generated. The sum of such nodes and their connections form a routing graph. As an example, with one node of in total more than 100,000 nodes it is described how this point gets the maximum vessel length and draft assigned.
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January 10, 2024
No items found.
Composition, spatial distribution and sources of macro-marine litter on the Gulf of Alicante seafloor (Spanish Mediterranean)
The composition, spatial distribution and source of marine litter in the Spanish Southeast Mediterranean were assessed. The data proceed from a marine litter retention programme implemented by commercial trawlers and were analysed by GIS.
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January 10, 2024
No items found.
Climate change, non-indigenous species and shipping: assessing the risk of species introduction to a high-Arctic archipelago
Anticipated changes in the global ocean climate will affect the vulnerability of marine ecosystems to the negative effects of non-indigenous species (NIS)
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January 15, 2024
No items found.
The Big Picture: An Improved Method for Mapping Shipping Activities
In this work, we propose a novel algorithmic framework for generating highly accurate density maps of shipping activities, from incomplete data collected by the Automatic Identification System (AIS).
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