Advancing Maritime Surveillance and Pollution Management

The IRSAI project in Cyprus aims to pioneer innovative technologies for maritime surveillance, pollution detection, and management. These technologies have not been previously demonstrated in Cyprus or globally. The project seeks to identify limitations, reduce uncertainties, validate effectiveness, understand how they work together, and optimize their operational use. Currently, the technologies are at Technological Readiness Level (TRL) 4 to 5, indicating lab validation but no operational demonstration. The goal is to raise the TRL to 7 by demonstrating prototype systems in an operational environment, bringing them closer to practical use.

1

Detection 

The project uses artificial intelligence to detect spillages in eastern Mediterranean waters, utilizing drone images and videos. CYENS, specializing in image and video processing, will develop and adapt these algorithms.
2

Sampling

Regarding the sampling part with the Unmanned Surface Vehicle (USV), IRSAI will build upon previous USVs developed at the RAS Lab. A new control unit will be designed for the proposed USV, incorporating navigation sensors for this application and an innovative oil detection sub-system. The new controller will be capable of receiving commands from human operators and target positions from the drone, allowing it to operate remotely or autonomously.
3

Forecasting 

The project will incorporate real-time, high-resolution, intelligently processed remote sensing data obtained by the drone into a state-of-the-art oil dispersion model for forecasting purposes. Although there are oil dispersion models on the market, most of them rely on satellite data, which might not be tactical and have poorer image quality. IRSAI seeks to test and enhance the model parameters through the integration of real-time current data, hence enabling more precise projections of pollution dispersion in maritime environments.