Online Event Recognition from Moving Vessel Trajectories

TL;DR

This paper introduces a real-time maritime monitoring system that tracks vessel trajectories, detects critical events, and provides instant alerts to authorities, validated through extensive tests on real and synthetic data.

Contribution

The paper presents a novel online system for maritime activity monitoring that combines trajectory tracking and complex event recognition for real-time alerts.

Findings

System performs efficiently on large-scale datasets.

Accurately detects emergencies like collisions and suspicious activities.

Validated through real-world vessel data and synthetic scenarios.

Abstract

We present a system for online monitoring of maritime activity over streaming positions from numerous vessels sailing at sea. It employs an online tracking module for detecting important changes in the evolving trajectory of each vessel across time, and thus can incrementally retain concise, yet reliable summaries of its recent movement. In addition, thanks to its complex event recognition module, this system can also offer instant notification to marine authorities regarding emergency situations, such as risk of collisions, suspicious moves in protected zones, or package picking at open sea. Not only did our extensive tests validate the performance, efficiency, and robustness of the system against scalable volumes of real-world and synthetically enlarged datasets, but its deployment against online feeds from vessels has also confirmed its capabilities for effective, real-time maritime surveillance.