Big Data Analytics for Time Critical Mobility Forecasting (datACRON) PDF Print E-mail
Written by Harris Georgiou   
Tuesday, 06 October 2009 22:45

Big Data Analytics for Time Critical Mobility Forecasting (datACRON)


datACRON (Big Data Analytics for Time Critical Mobility Forecasting) is a research and innovation collaborative project introducing novel methods for threat and abnormal activity detection in very large fleets of moving entities spread across large geographical areas.Specifically, datACRON aims to develop novel methods for real-time detection and prediction of trajectories and important events related to moving entities, together with advanced visual analytics methods, over multiple heterogeneous, voluminous, fluctuating, and noisy data streams from moving entities, correlating them with archived data expressing, among others, entities’ characteristics, geographical information, mobility patterns, regulations and intentional data (e.g. planned routes), in a timely manner. Technological developments are validated and evaluated in user-defined challenges focusing on increasing the safety, efficiency and economy of operations concerning moving entities in the Air-Traffic Management and Maritime domains. The datACRON project brings together partners from academia and industry to develop the aforementioned novel methods, together with user and data-provision partners from the two domains, in close relation to user-interest groups, focusing on real-life, industrial and user-defined challenges concerning operations (e.g. surveillance, forecasting of trajectories, characterization, etc.) regarding moving entities in sea and air.
Keywords: air traffic control, maritime surveillance, trajectory prediction, data analytics


Notice: The DART project is currently under development. Publication of all the material and results related to this work is limited due to IPR limitations, until the last stages of the project by the end of 2017. Any material that is accessible here is granted under the terms of the copyright notice included in this page.

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Last Updated on Wednesday, 25 October 2017 11:19