Multi-Criteria Surveillance AI-based Scheduling Analytics for Undersea Infrastructure Safety

This study will look into research methods and algorithms for protection of critical undersea infrastructure from a logistical perspective. The problem addresses the vulnerability of electricity, internet, oil and gas undersea cables to interferences, attacks, and environmental factors. There is a need for an integrated randomised surveillance strategy that combines information obtained from UAVs, UUVs, surface vessels, satellites, and sensors. The problem is at least bi-objective in nature as there is a trade-off between resource cost and incident detection probability. This work aims at developing a prototype surveillance scheduling algorithm with machine learning. Our case study will include one or two of the electricity interconnector, internet or gas and oil pipelines, that run between the UK and Norway.

Funding: Themes Research and Innovation (TRIF) 2023/24 £54,965.00