Ricerc@Sapienza

The aim of the research is to design and optimize multimedia underwater sensor networks for smart monitoring of remote marine energy generation plants made of underwater turbines exploiting sea currents for generating energy.

By relying on a combination of research ideas on machine learning-based optimisation of underwater wireless networks (to transmit in real-time monitored data) as well as on processing and compression of sensor data and underwater images, the BLUENERGY project has the ambition to pose the scientific foundations for the development of automated, remote and real-time, monitoring systems enabling predictive and preventative operation and maintenance for the offshore renewable energy sector.

In our reference scenario underwater turbines are deployed in shallow water. Each turbine is instrumented with sensors, e.g., on the turbine blade, on the moorings, to monitor structural integrity, as well as with video-cameras.

Our objective is to study where to place the sensors, how to compress information and how to transmit it in real-time in presence of significant noise and fast varying channel conditions, to be able to provide the needed level of granularity of information required for risk assessment and forecasting, for system operation and maintenance optimisation. To achieve this challenging objective the project relies on a multidisciplinary team of internationally recognised researchers in three scientific area, coming from two different macro-areas (D and F), covering the field of sensing systems and networking, computer vision, multimedia and computer graphics.

The project will provide both fundamental results (algorithms, protocols) and experimental ones. The designed solutions will be validated through: a) testing of the effectiveness of the information compression and reconstruction techniques on datasets of underwater data and images; b) system simulations; c) small scale field experiments.