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Anomaly Detection and Complex Event Processing Over IoT Data Streams - Research Book

Anomaly Detection and Complex Event Processing Over IoT Data Streams

Great Research Book in Anomaly Detection and Complex Event Processing Over IoT Data Streams

Author(s) Name:  Patrick Schneider, Fatos Xhafa

About the Book:

   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 and the anomaly detection algorithms over them. 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. The book comprises fundamental models, concepts and algorithms, architectures and technological solutions as well as their application to eHealth. Case studies, such as the bio-metric signals stream processing are presented –the massive amount of raw ECG signals from the sensors are processed dynamically across the data pipeline and classified with modern machine learning approaches including the Hierarchical Temporal Memory and Deep Learning algorithms. The book discusses adaptive solutions to IoT stream processing that can be extended to different use cases from different fields of eHealth, to enable a complex analysis of patient data in a historical, predictive and even prescriptive application scenarios. The book ends with a discussion on ethics, emerging research trends, issues and challenges of IoT data stream processing.

Table of Contents

  • Chapter 1: IoT data streams: concepts and models
  • Chapter 2: Data stream processing: models and methods
  • Chapter 3: Anomaly detection
  • Chapter 4: Complex event processing
  • Chapter 5: Rule-based decision support systems for eHealth
  • Chapter 6: Integrating technological solutions into innovative eHealth applications
  • Chapter 7: IoT, edge, cloud architecture and communication protocols
  • Chapter 8: Machine learning
  • Chapter 9: Anomaly detection, classification and CEP with ML methods
  • Chapter 10: Architectures and technologies for stream processing
  • Chapter 11: Technical design: data processing pipeline in eHealth
  • Chapter 12: Working procedure and analysis for an ECG dataset
  • Chapter 13: Ethics, emerging research trends, issues and challenges
  • ISBN:  9780128238189

    Publisher:  Elsevier

    Year of Publication:  2022

    Book Link:  Home Page Url