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
Global Oceans 2020: Singapore – U.S. Gulf Coast, 2020
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.
Published in the journal Internationales Verkehrswesen Issue 2 | 2022
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.
Authors: Prof. Dr. Sönke Reise, Dr. Carsten Hilgenfeld, Diego Piedra-Garcia
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.
Authors: Maximilian Held, Boris Stolz, Jan Hoffmann, Gil Georges, Michele Bolla, Konstantinos Boulouchos
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.
Authors: Boris Stolz, Maximilian Held, Konstantinos Boulouchos
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.
Authors: Carsten Hilgenfeld, Nina Vojdani, Frank Heymann, Evamarie Wiessner, Bettina Kutschera, Chris Bünger
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.
Authors: Santiago García-Rivera, Jose Luis Sánchez Lizaso, Jose María Bellido Millán
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)
Authors: Chris Ware, Jørgen Berge, Jan H. Sundet, Jamie B. Kirkpatrick, Ashley D. M. Coutts, Anders Jelmert, Steffen M. Olsen, Oliver Floerl, Mary S. Wisz, Inger G. Alsos
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).
GMSA: A Digital Twin Application for Maritime Route and Event Forecasting
Digital twins are increasingly valuable in sectors like maritime,energy, logistics and transportation. In the maritime industry, the complexity of monitoring vessel traffic, necessitates more sophisticated, data-driven approaches due to the high volume of vessels and intricate movement patterns. This paper introduces GMSA, adigital twin application for maritime route and event forecasting for the entire global fleet, utilizing the real-time AIS streaming service of Kpler (MarineTraffic), for maritime event detection, vessel route prediction and traffic state estimation. Through the combined views of the real-time event detection functions, the vessel and port-specific data driven models, and the visualization of historical aggregated vessel mobility metrics, the application creates a a multi-layer information system for efficient, proactive action planning and enhanced decision making for the end-user.
A Scalable System for Maritime Route and Event Forecasting
Digital twins serve as virtual representations of physical environments that are increasingly valuable across various sectors, including maritime operations. The complexity of monitoring vessel traffic through the Automatic Identification System (AIS), demands more sophisticated, data-driven approaches due to the extreme vessel volume and intricate vessel movement patterns.
Patterns of Life : Global Inventory for maritime mobility patterns
More than 70% [22] of the global trade transportation is conducted by sea, through maritime sea lanes. Unlike the well defined global land transportation network that consists of roads and railways, the maritime equivalent consists of port connections and is vaguely defined by marine charts’ guidelines, constraints and common sea routes. By definition, the port of origin and port of destination are well defined locations. However, the routes that the vessels follow in between are not strictly defined. Local conditions, such as the weather or traffic congestion, vessel-specific characteristics or other external conditions also affect the route choice and planning.