Online anomaly detection for sensor systems: A simple and efficient approach

Wireless sensor systems aid scientific studies by instrumenting the real world and collecting measurements. Given the large volumes of measurement collected by sensor systems, one problem arises, namely an automated approach to identifying the “interesting” parts of these data sets, or anomaly detection. A good anomaly detection methodology should be able to accurately identify many types of anomalies, be robust, require relatively little resources, and perform detection in (near) real-time. Thus, in this paper we focus on an approach to online anomaly detection in measurements collected by sensor systems (that exhibits these characteristics) and on its evaluation.