Integrated System for Interoperable sensors & Information sources for Common abnormal vessel behaviour detection & Collaborative identification of threat

Projet FP7, Appel SEC-2009-1

Objectives of the Research Project

The I2C integration project proposes for 2015 a new generation of innovative sea border surveillance systems implementing key existing and in development capacities to track all vessel movements to early identify and report on threats associated with detected suspicious events. These key capacities are:

• Shore based sensors platform grouping new sensor technologies; long range HFSW radar, FMCW radar to track small crafts (both prototypes are in experimentation), AIS stations and conventional coastal radar. This platform performs a permanent all weather traffic surveillance over wide maritime zone up to 200 nautical miles.
• Deployable sensors platforms to perform local node observation campaigns to complete shore based surveillance. Four equipped platforms are deployed; aircraft and vessel patrols, USV and Zeppelin, which offers absolute quiet flight with no vibration for high resolution observation quality and a payload of 2 tons for sensors and communication devices.
• Capacity for a common operational traffic picture to correlate vessels tracks from shore based and deployable sensors plots.
• Capacity for common intelligent operational traffic picture appending to vessel tracks information on performed activities, flags, sea state conditions, regulations, etc.
• Capacity to detect abnormal vessel behaviours and automatically issue alarms to operator for validation. Detection is based on multi-parameter rules and detection engines.
• Capacity to understand suspicious events, identify threats early and issue periodically interpretation files to authorities for decision.
• Capacity to transfer useful data sets through a communication network based on Distributed Systems intercommunication Protocol (DSiP) and VSAT/Digital Video Broadcast technologies.

More specifically, SMAC will use the AMAS technology to find new algorithms able to learn and detect abnormal vessel behaviours from the common intelligent operational traffic picture. Documented alarms will also be generated automatically for operational validation.