DocumentCode :
3717231
Title :
How not to drown in a sea of information: An event recognition approach
Author :
Elias Alevizos;Alexander Artikis;Kostas Patroumpas;Marios Vodas;Yannis Theodoridis;Nikos Pelekis
Author_Institution :
Institute of Informatics & Telecommunications, NCSR Demokritos, Athens, Greece
fYear :
2015
Firstpage :
984
Lastpage :
990
Abstract :
Maritime monitoring is a typical Big Data problem where hundreds of thousands of vessels across the globe transmit messages about their location, speed and other information. We have developed a system for online vessel tracking that performs, as a first step, a high-rate but accurate trajectory compression. Subsequently, the compressed trajectories are analyzed by a complex event recognition engine, promptly reporting alerts to maritime authorities. To deal with realistic maritime event patterns, we seamlessly integrated spatial and temporal reasoning for online event recognition. The system is evaluated on real data from the Greek seas.
Keywords :
"Trajectory","Cognition","Surveillance","Ports (Computers)","Big data","Calculus"
Publisher :
ieee
Conference_Titel :
Big Data (Big Data), 2015 IEEE International Conference on
Type :
conf
DOI :
10.1109/BigData.2015.7363849
Filename :
7363849
Link To Document :
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