Friday 3 July 2026

ADAPT celebrated success at the Analytics & AI Awards 2026 recently, with its 'Sea-Scan: Dark Vessel Identification Using AI-Enhanced Sensing Over Telecommunication' project taking home the Innovation Award.

The Sea-Scan initiative is led by Professor Marco Ruffini of the School of Computer Science and Statistics and Dr John Kennedy of the School of Engineering at Trinity College Dublin. The project is developing advanced real-time vessel detection technology designed to strengthen maritime monitoring and security capabilities.

Large-scale sensing network

Sea-Scan explores the use of existing subsea fibre-optic telecommunications cables to create a large-scale sensing network. Using a technique known as Distributed Acoustic Sensing (DAS), researchers send pulses of light through fibre-optic cables and analyse minute changes in the returning signal. These fluctuations can reveal vibrations in the water and seabed, effectively transforming telecommunications infrastructure into a continuous underwater sensing system.

The project combines this sensing capability with artificial intelligence and machine learning models trained to recognise the acoustic signatures of vessels of varying sizes, engine types and operating characteristics. The goal is to develop a fully autonomous 24/7 maritime monitoring and early warning system capable of identifying suspicious or “dark” vessels operating in Irish and European waters.

Sea-Scan is expected to deliver significant national, economic and environmental benefits. By enabling continuous ocean monitoring, the technology could strengthen the situational awareness of the Defence Forces and support the protection of critical maritime infrastructure. The system also enhances the resilience of Ireland’s digital infrastructure by improving the early detection of unusual offshore activity, providing reassurance to authorities, infrastructure operators and international investors.

Economically, the project offers a cost-effective approach by repurposing existing subsea cable infrastructure rather than requiring the deployment of new offshore hardware. Environmentally, continuous sensing capabilities could help reduce cable damage risks while also supporting broader marine environmental monitoring initiatives.

L-R: Dr John Kennedy and Professor Marco Ruffini with award.