SELF-SUPERVISED LEARNING FOR REFRIGERATION SYSTEM MONITORING IN IIOT

This thesis evaluates self-supervised, semi-supervised, supervised, and rule-based machine learning approaches for anomaly detection in low-frequency LoRaWAN refrigeration monitoring across 84 sensors.