Wireless Sensor Networks (WSNs) can experience problems (anomalies) during deployment, due to dynamic environmental factors or node hardware and software failures. These anomalies demand reliable detection strategies for supporting long term and/or large scale WSN deployments. Several strategies have been proposed for detecting specific subsets of WSN anomalies, yet there is still a need for more comprehensive anomaly detection strategies that jointly address network, node, and data level anomalies. This chapter examines WSN anomalies from an intelligent-based system perspective, covering anomalies that arise at the network, node and data levels. It generalizes a simple process for diagnosing anomalies in WSNs for detection, localization, and root cause determination. A survey of existing anomaly detection strategies also reveals their major design choices, including architecture and user support, and yields guidelines for tailoring new anomaly detection strategies to specific WSN application requirements.