Part I - Fundamental concepts, models and methods 1. IoT data streams: concepts and models 2. Data stream processing: models and methods 3. Anomaly detection 4. Complex event processing 5. Rule-based decision support systems for e-health
Part II - Architectures and technological solutions 6. State of the art in technological solutions for e-health 7. IoT, edge, cloud architecture and communication protocols 8. Machine learning 9. Anomaly detection, classification and complex event processing
Part III - Case study: scalable IoT data processing and reasoning ecosystem in the field of health 10. Conceptual design: architecture 11. Technical design: data processing 12. Working procedure and analysis for an ECG dataset 13. Ethics, emerging research trends, issues and challenges