System for detecting abnormal operating states of a heating system

Detection of anomalous operating states of a temperature control system (e.g. a central heating system, fig 1) is performed using a prediction model. The model is trained using training samples based on operational data of the system 702. The training samples contain values for training features derived from operational data which are processed using an anomaly detection model, which outputs an anomaly score that is indicative of an anomalous outlier. An anomaly indication is associated with each anomaly score. The prediction model is then trained 710 on the processed training samples and anomaly indications so that it may predict a corresponding anomaly indication for a test sample of feature values. The prediction model is then used to identify an anomalous operating state of a temperature control system being monitored based on further operational data received from the monitored temperature control system.