An Intelligent Framework for Vessel Traffic Monitoring Using AIS Data

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.