Anomaly Detection and Complex Event Processing over IoT Data Streams: With Application to Electrocardiogram Patient Data Monitoring

Anomaly Detection and Complex Event Processing over IoT Data Streams: With Application to Electrocardiogram (ECG) 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. Provides the state-of-the-art in IoT Data Stream Processing, Semantic Data Enrichment, Reasoning and KnowledgeCovers extraction (Anomaly Detection)Illustrates new, scalable and reliable processing techniques based on IoT stream technologiesOffers applications to new, real-time anomaly detection scenarios in the health domain INDICE: 1. Related work and literature review 2. IoT Stream processing and Semantic Processing 3. IoT, Edge and Cloud Architecture 4. Case Study: Scalable IoT data processing and reasoning ecosystem in the field of Health 5. Communication protocols 6. Conceptual Design: Architecture 7. Technical design: Data Processing - ECG Data 8. Anomaly detection, classification and complex event processing 9. Computational Results and Analysis 10. Rule-based Software Systems for eHealth 11. Emerging Research Issues and Challenges 12. Conclusions

• ISBN: 978-0-12-823818-9
• Editorial: Academic Press
• Encuadernacion: Rústica
• Páginas: 270
• Fecha Publicación: 01/06/2021
• Nº Volúmenes: 1
• Idioma: Inglés