A Bayesian Learning Approach for Drone Coverage Network: A Case Study on Cardiac Arrest in Scotland

ArXi:2603.23134v1 Announce Type: new Drones are becoming popular as a complementary system for \ac{ems}. Although several pilot studies and flight trials have shown the feasibility of drone-assisted \ac{aed} delivery, running a full-scale operational network remains challenging due to high capital expenditure and environmental uncertainties. In this paper, we formulate a reliability-informed Bayesian learning framework for designing drone-assisted \ac{aed} delivery networks under environmental and operational uncertainty.