Neural-Fuzzy Inference Engine for Maritime Anomaly Detection

In an era of heightened security concerns, a vast
amount of data concerning vessel activity is
collected. However, the ability for aggregation and
real-time analysis for every vessel in a port or
waterway is limited by availability of personnel and
human capability for real-time analysis. An automated
decision tool can alleviate some of the processing
burden by providing maritime personnel with detection
alerts that indicate unusual vessel activity and
direct personnel focus to problem areas. The system
is referred to as VASE (Vessel Anticipatory
Situation-Awareness Engine).VASE provides an
automated detection tool that uses spatial and
kinematics indicators to detect unusual vessel
activity. The system overlays machine learning
techniques on maritime data streams to provide alerts
of unusual indicators usable by maritime personnel.
These indicators include unusual changes in speed,
course, or proximity to other maritime objects. With
these alerts, maritime personnel would be able to
determine the appropriate course of action, such as
contacting a vessel, allocating commandable sensors
to a vessel of interest, or performing further
investigation with other sources.

Autorentext
Dr. Novellus serves as a Risk Management Consultant for several government agencies. She received Bachelors in Computer Engineering and Economics from the University of California,Santa Cruz, a Masters in Information Technology from Rensselaer Polytechnic Institute, and a Doctorate in Systems Engineering from the George Washington University.

Klappentext
In an era of heightened security concerns, a vast amount of data concerning vessel activity is collected. However, the ability for aggregation and real-time analysis for every vessel in a port or waterway is limited by availability of personnel and human capability for real-time analysis. An automated decision tool can alleviate some of the processing burden by providing maritime personnel with detection alerts that indicate unusual vessel activity and direct personnel focus to problem areas. The system is referred to as VASE (Vessel Anticipatory Situation-Awareness Engine).VASE provides an automated detection tool that uses spatial and kinematics indicators to detect unusual vessel activity. The system overlays machine learning techniques on maritime data streams to provide alerts of unusual indicators usable by maritime personnel. These indicators include unusual changes in speed, course, or proximity to other maritime objects. With these alerts, maritime personnel would be able to determine the appropriate course of action, such as contacting a vessel, allocating commandable sensors to a vessel of interest, or performing further investigation with other sources.