We are passionate about supporting research partners and academic staff in their research projects. Many scientific papers and publications have been based on FleetMon data sources. Please find a collection of the latest publications accomplished with the assistance of FleetMon.
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.
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.
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.
FleetMon Supports the Development of Environmental Impact Assessment on the Brazilian Coast
Authors: Dr. Daniel Zacharias, Dr. Adalgiza Fornaro, Maíra Pippus and Tanja Lohrmann
Scrapping Probabilities and Committed CO2 Emissions of the International Ship Fleet
Authors: Maximilian Held, Boris Stolz, Jan Hoffmann, Gil Georges, Michele Bolla, Konstantinos Boulouchos Abstract: Fighting climate change demands action in all sectors. International shipping faces
The CO2 reduction potential of shore-side electricity in Europe
Authors: Boris Stolz, Maximilian Held, Konstantinos Boulouchos Abstract: Shore-side electricity can drastically reduce the emissions from fossil fuel-powered auxiliary engines of ships at berth. Data
Estimation of worldwide ship emissions using AIS signals
Authors: Constance Ugé, Tina Scheidweiler, Carlos Jahn Abstract: The reduction of emissions is one of the main common goals all over the globe. Shipping, as
Scalable In-Database Machine Learning for the Prediction of Port-to-Port Routes
Authors: Dennis Marten, Carsten Hilgenfeld, Andreas Heuer Abstract: The correct prediction of subsequential port-to-port routes plays an integral part in maritime logistics and is therefore essential
Green shipping: using AIS data to assess global emissions
Authors: Constance Ugé, Carlos Jahn Abstract: Globalization and new environmental legislations lead to a rising need for new technological developments for the shipping industry, especially
How a real-time-based sea traffic forecast helps to organize and optimize the flow of maritime goods
Author: Dana Meißner Abstract: As part of the PRESEA research project, which began in summer 2019, a real-time-based sea traffic forecast application is to be
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
Authors: Carsten Hilgenfeld, Nina Vojdani, Frank Heymann, Evamarie Wiessner, Bettina Kutschera, Chris Bünger Abstract: For the international exchange of goods, an exact estimated time of
Composition, spatial distribution and sources of macro-marine litter on the Gulf of Alicante seafloor (Spanish Mediterranean)
Authors: Santiago García-Rivera, Jose Luis Sánchez Lizaso, Jose María Bellido Millán Abstract: The composition, spatial distribution and source of marine litter in the Spanish Southeast
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