Overview

Pattern and Anomaly Detection Engine (PADE) detects potential threats by analyzing historical vessel movements using a statistical behavior model. PADE applies this pattern analysis to detect and alert anomalous vessel movement within the context of geography, time of year and sea conditions.

With PADE, you do not have to rely on a vessel to broadcast its destination. PADE will predict a vessel’s likely destination port based on statistical analysis of prior vessel behavior. PADE will also backtrack a vessel’s path to likely ports of origin.

Pattern Awareness

PADE gives you the pattern of life information you need for mission success:

Predicted Destination Determine a vessel's likely destination based on statistical analysis of prior vessel behavior
Derived Origin Determine a vessel's likely origin port based vessel track history
Port to Port A breakdown of vessel origins and destinations for each port
Occupancy A breakdown of vessel by category that have been observed in every plot of ocean

Kinetic alerts

PADE can detect the following vessel movement anomalies:

Non-Optimal Route Taken When a vessel has travelled a path significantly less optimal than its Great Circle Route
Unusual Speed of Advance When a vessel changes speed significantly, either slowing down or speeding up
Route Change Indicator When the expected destination port for a vessel changes mid course
Abrupt Course Changes When a vessel makes a significant change in heading
Loitering When a vessel stops while away from a port and from land

Interoperability

PADE is compatible with DEIP, DEIPER, HDA-DEIP and Targetr, as well as Google Maps™, Google Earth™, and other systems that accept KML. PADE’s web services provide additional data for visualization and analysis, including port-to-port vessel traffic, expected destination of vessels, images and details about the vessel.

Loitering Alert
Real Time Updates
Route and Destination Prediction
Multiple Route Possibilities
Global Movement Model