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Vessels in open seas are seldom continuously observed. Thus, the problem of long-term vessel prediction becomes crucial. This paper focuses its attention on the performance assessment of the Ornstein-Uhlenbeck target motion model comparing it with the well-established nearly constant velocity model. A gating association procedure and proper performance metrics are introduced to assess the performance...
We describe how we leveraged best practices in big data processing pipeline design and visual analytics to prototype the Maritime Patterns-of-Life Information Service (MPoLIS), an information product currently under development at the NATO Centre for Maritime Research and Experimentation (CMRE). MPoLIS supports the maritime industry, governments, and international organizations with visual analytics...
Seaports are spatial units that do not remain static over time. They are constantly in flux, evolving according to environmental and connectivity patterns both in size and operational capacity. As such any valid decision making regarding port investment and policy making, essentially needs to take into account port evolution over time and space, thus, accurately defining a seaport's exact location,...
Seaports play a vital role in the global economy, as they operate as the connection corridors to all other modes of transport and as engines of growth for the wider region. But ports today are faced with numerous unique challenges and for them to remain competitive, significant investments are required. In support of greater transparency in policy making, decisions regarding investment need to be...
Computational Maritime Situational Awareness (MSA) supports the maritime industry, governments, and international organizations with machine learning and big data techniques for analyzing vessel traffic data available through the Automatic Identification System (AIS). A critical challenge of scaling computational MSA to big data regimes is integrating the core learning algorithms with big data storage...
Driven by real-world issues in maritime surveillance, we consider the problem of estimating the target state from a sequence of observations that can be imprecisely time-stamped. That is, the time between two consecutive observations can be affected by an unknown error or delay. We propose an adaptive filtering strategy able to sequentially detect the time delays and correctly estimate the target...
This paper presents the recent developments of an Optimal Path Planning — Decision Support System (OPP-DSS). The designed framework is based on multi-objective optimization algorithms providing a set of Pareto efficient solutions representing a trade-off among mission objectives. Meteorological and Oceanographic (METOC) and Automatic Identification System (AIS) vessel traffic data are integrated and...
Traffic route analysis and prediction are both crucial to maritime security. The ability to predict a vessel position in the future is essential to provide information on upcoming events. However, accurate prediction along a route is a challenging task in the maritime domain, due to the complex nature and variability of traffic patterns. Based on the popular Ornstein-Uhlenbeck stochastic mean-reverting...
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