Jan A. Persson

Online Unsupervised Anomaly Detection with Model Explainability and Human-in-the-Loop Feedback

Smart building IoT networks generate complex, continuous sensor streams that challenge traditional anomaly detection due to concept drift and limited interpretability. This project proposes and validates an online, unsupervised, and human-refinable anomaly detection architecture. The system uses a parallel inference en...