Anomaly Detection and Complex Event Processing over IoT Data Streams: With Application to eHealth and Patient Data Monitoring presents advanced processing techniques for IoT data streams. The book brings new advances and generalized techniques for processing IoT data streams, semantic data enrichment with contextual information at Edge, Fog and Cloud as well as complex event processing in IoT applications. Bio-metric signals, such as the massive amount of raw ECG signals from the sensors are processed dynamically across the data pipeline and classified with modern machine learning approaches based on the Hierarchical Temporal Memory (HTM) and Convolutional Neural Network (CNN) algorithms.The book discusses adaptive solutions that can be extended to other use cases to enable a complex analysis of patient data in a historical, predictive and even prescriptive application scenario.