Ensemble based sensing anomaly detection in wireless sensor networks

► We developed an efficient ensemble of five classifiers to detect sensor anomalies. ► We model the correct sensor behavior in complex/dynamic environments using five models. ► We solve the problems related to training, testing and evaluation of the ensemble. ► Our ensemble offers reliable estimations to replace the erroneous measurements. ► We present a case study to show the preciseness of our method.