Real-Time Data Analytics for Large Scale Sensor Data

Real-Time Data Analytics for Large Scale Sensor Data

by Himansu Das, Nilanjan Dey, Valentina Emilia Balas
Released August 2019
Publisher(s): Academic Press
ISBN: 9780128182420

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Book description

Real-Time Data Analytics for Large-Scale Sensor Data covers the theory and applications of hardware platforms and architectures, the development of software methods, techniques and tools, applications, governance and adoption strategies for the use of massive sensor data in real-time data analytics. It presents the leading-edge research in the field and identifies future challenges in this fledging research area. The book captures the essence of real-time IoT based solutions that require a multidisciplinary approach for catering to on-the-fly processing, including methods for high performance stream processing, adaptively streaming adjustment, uncertainty handling, latency handling, and more.

  • Examines IoT applications, the design of real-time intelligent systems, and how to manage the rapid growth of the large volume of sensor data
  • Discusses intelligent management systems for applications such as healthcare, robotics and environment modeling
  • Provides a focused approach towards the design and implementation of real-time intelligent systems for the management of sensor data in large-scale environments

Table of contents

  1. Cover image
  2. Title page
  3. Table of Contents
  4. Copyright
  5. Contributors
  6. Preface
  7. Chapter 1: Internet of Things in healthcare: Smart devices, sensors, and systems related to diseases and health conditions
    1. Abstract
    2. Graphical Abstract
    3. 1.1 Introduction
    4. 1.2 Material and methods
    5. 1.3 Results
    6. 1.4 Discussion
    7. 1.5 Conclusion
  8. Chapter 2: Real-time data analytics in healthcare using the Internet of Things
    1. Abstract
    2. Acknowledgments
    3. 2.1 Introduction
    4. 2.2 Computing system of IoT technology in healthcare activities
    5. 2.3 Proposed model and its implementation
    6. 2.4 Working mechanism of device
    7. 2.5 Uses and discussion of the device
    8. 2.6 Conclusion
  9. Chapter 3: Lightweight code self-verification using return-oriented programming in resilient IoT
    1. Abstract
    2. Acknowledgments
    3. 3.1 Introduction
    4. 3.2 Preliminaries
    5. 3.3 Resilient IoT network
    6. 3.4 Code tamper-proofing
    7. 3.5 Experimental result
    8. 3.6 Conclusion
  10. Chapter 4: Monte-Carlo Simulation models for reliability analysis of low-cost IoT communication networks in smart grid
    1. Abstract
    2. 4.1 Introduction
    3. 4.2 Overview of wireless IoT communication networks for PMUs
    4. 4.3 Monte-Carlo simulation models
    5. 4.4 Optimum PMU placement
    6. 4.5 Case study
    7. 4.6 Conclusion and directions for future research
  11. Chapter 5: Lightweight ciphertext-policy attribute-based encryption scheme for data privacy and security in cloud-assisted IoT
    1. Abstract
    2. 5.1 Introduction
    3. 5.2 Related work
    4. 5.3 Preliminaries
    5. 5.4 System model
    6. 5.5 Construction of LCP-ABE
    7. 5.6 Security analysis
    8. 5.7 Performance analysis
    9. 5.8 Conclusion
  12. Chapter 6: Soft sensor with shape descriptors for flame quality prediction based on LSTM regression
    1. Abstract
    2. 6.1 Introduction
    3. 6.2 Literature survey
    4. 6.3 Description of flame shape and burner system
    5. 6.4 LSTM for flame shape-based combustion quality prediction model
    6. 6.5 Objective of the work
    7. 6.6 Hypothesis of this work
    8. 6.7 Experimental environment and data preparation
    9. 6.8 Experimental results and discussion
    10. 6.9 Conclusion
  13. Chapter 7: Communication-aware edge-centric knowledge dissemination in edge computing environments
    1. Abstract
    2. Acknowledgments
    3. 7.1 Introduction
    4. 7.2 Literature review
    5. 7.3 Rationale and fundamentals
    6. 7.4 Methodology
    7. 7.5 Experimental design
    8. 7.6 Results and evaluation
    9. 7.7 Conclusions and future work
  14. Chapter 8: An effective blockchain-based, decentralized application for smart building system management
    1. Abstract
    2. 8.1 Introduction
    3. 8.2 Background
    4. 8.3 Overall design structure
    5. 8.4 System implementation
    6. 8.5 A proof-of-concept case study
    7. 8.6 Related work
    8. 8.7 Conclusion and future work
  15. Chapter 9: Privacy and security of Internet of Things devices
    1. Abstract
    2. 9.1 Introduction
    3. 9.2 The need for security
    4. 9.3 Creating and maintaining trusted execution environments (TEE)
    5. 9.4 Security by separation
    6. 9.5 Blockchain for trusted communication
    7. 9.6 Context-aware security
    8. 9.7 Technologies integration in a comprehensive security architecture for IoT devices
    9. 9.8 Literature review
    10. 9.9 Conclusion
  16. Chapter 10: Software-Defined Networking for the Internet of Things: Securing home networks using SDN
    1. Abstract
    2. 10.1 Introduction
    3. 10.2 Methodology
    4. 10.3 System design
    5. 10.4 Results
    6. 10.5 Conclusion
    7. Appendix 1: Implementation screenshots
  17. Index

Product information

  • Title: Real-Time Data Analytics for Large Scale Sensor Data
  • Author(s): Himansu Das, Nilanjan Dey, Valentina Emilia Balas
  • Release date: August 2019
  • Publisher(s): Academic Press
  • ISBN: 9780128182420