  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.

Computer Vision and Pattern Recognition;Artificial Intelligence