Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/29883
Title: | An Intelligent Framework for Vessel Traffic Monitoring Using AIS Data | Authors: | Evmides, Nicos Odysseos, Lambros Michaelides, Michalis P. Herodotou, Herodotos |
Major Field of Science: | Engineering and Technology | Field Category: | Electrical Engineering - Electronic Engineering - Information Engineering | Keywords: | Estimation;Data collection;Real-time systems;Risk management;Artificial intelligence;Collision avoidance;Monitoring | Issue Date: | 6-Jun-2022 | Source: | Proceedings of 23rd IEEE International Conference on Mobile Data Management, MDM 2022, 6 - 9 June, Paphos, Limassol, pp. 413-418 | Start page: | 413 | End page: | 418 | Journal: | 23rd IEEE International Conference on Mobile Data Management | Abstract: | Automatic identification system (AIS) data provides a wealth of information regarding vessel traffic and is used for a variety of applications such as collision detection and avoidance, route prediction and optimization, search and rescue operations, etc. However, several challenges exist when working with AIS data including huge volume and velocity (as AIS signals are sent by vessels every few seconds), message duplication, various types of data irregularities, as well as the need for real-time processing and analysis. This paper presents a new framework for collecting, processing, storing, and analyzing AIS data in real time plus a set of algorithms for doing so in an efficient and scalable way. At the same time, a set of intelligent services are provided as building blocks for improving and creating new AIS data driven applications. This framework has been operational for the past few years in Cyprus, and has collected and processed around one billion AIS messages from the Eastern Mediterranean Sea. | URI: | https://hdl.handle.net/20.500.14279/29883 | ISBN: | 9781665451765 | ISSN: | 15516245 | DOI: | 10.1109/MDM55031.2022.00091 | Rights: | © Copyright IEEE - All rights reserved. | Type: | Conference Papers | Affiliation : | Cyprus University of Technology | Publication Type: | Peer Reviewed |
Appears in Collections: | Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation |
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