Table of Contents

Part I - Fundamental concepts, models and methods1. IoT data streams: concepts and models2. Data stream processing: models and methods3. Anomaly detection4. Complex event processing5. Rule-based decision support systems for e-healthPart II - Architectures and technological solutions6. State of the art in technological solutions for e-health7. IoT, edge, cloud architecture and communication protocols8. Machine learning9. Anomaly detection, classification and complex event processingPart III – Case study: scalable IoT data processing and reasoning ecosystem in the field of health10. Conceptual design: architecture11. Technical design: data processing12. Working procedure and analysis for an ECG dataset13. Ethics, emerging research trends, issues and challenges

Feature

Provides the state-of-the-art in IoT Data Stream Processing, Semantic Data Enrichment, Reasoning and Knowledge Covers extraction (Anomaly Detection) Illustrates new, scalable and reliable processing techniques based on IoT stream technologies Offers applications to new, real-time anomaly detection scenarios in the health domain

Details