Francesco Vitale

An Embedded Testbed to Measure Energy and Accuracy in Federated Anomaly Detection Under Concept Drift: Special Session Paper

Anomaly detection at the edge increasingly relies on federated learning to share knowledge across resource-constrained devices. At the same time, concept drift forces deployed models to adapt as the definition of normality evolves. However, such approaches are typically validated in simulation, so their energy claims a...