Advanced tracking techniques can be powerful but heavy, requiring specialist expertise and significant computing resources. In many real surveillance settings, however, operators need lighter tools that are fast, transparent and easy to explain to non-experts.

The authors of this UnderSec-funded study propose a decision-support system that uses straightforward geometric and kinematic rules—such as maximum realistic speeds, distance thresholds, moving averages and continuity checks—to clean trajectories and highlight anomalies. It predicts the next likely position based on recent speed and heading and then compares new data points to this expectation, flagging large or repeated deviations that may indicate abrupt turns or other unusual behaviour.

For UnderSec, this lightweight and interpretable approach is valuable because it can be integrated into broader monitoring chains that follow vessel movements near critical and underwater infrastructures. It offers a practical way to support quick assessments and focus attention on potentially abnormal traffic without requiring complex model tuning.