GREAF: Graph-based Real-time Anomaly Detection via Forecasting for IoT-Enabled Indoor Spaces
The increasing deployment of IoT sensors in smart homes and offices enables data-driven automation while exposing these systems to sensor faults, abnormal user activities, and unexpected event patterns. Graph Neural Networks (GNNs) offer a principled way to model spatial dependencies among sensors, yet existing GNN-bas...