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Emerging Smart Technologies for Critical Infrastructure

  • Book
  • © 2023

Overview

Editors:
  1. Shantanu Pal

    1. School of Information Technology, Deakin University, Burwood, Australia

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  2. Zahra Jadidi

    1. School of Information and Comm Tech, Griffith University, Nathan, Australia

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  3. Ernest Foo

    1. School of Information and Comm Tech, Griffith University, Nathan, Australia

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  4. Subhas C. Mukhopadhyay

    1. School of Engineering, Macquarie University, Sydney, Australia

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  • Addresses academic researchers, developers and industry partners
  • Presents advances in Internet-of-Things and data engineering
  • Written by experts in the field

Part of the book series: Smart Sensors, Measurement and Instrumentation (SSMI, volume 44)

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About this book

This book highlights the latest advancements, innovation, technology, and real-world challenges and solutions related to smart critical infrastructure. In addition, it provides quantitative and qualitative research innovations to individual, academic, organizational and industry practitioners in a wide range of practical solutions using emerging technologies in areas such as smart sensing, data acquisition, data analytics, data processing, and other related topics, such as security, privacy, and trust to devices, users, and the systems. Finally, the book discusses the various societal applications using the Internet of Things and emerging technologies. As such, it offers an essential reference guide about the latest design and development in critical infrastructure for academia and industry. Fully explaining all the techniques used, the book is of interest to engineers, researchers, and scientists working in wireless sensor networks, Internet of Things systems, and emerging technologies.

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Table of contents (7 chapters)

  1. Front Matter

    Pages i-ix
    Download chapter PDF

  2. Cybersecurity for Satellite Smart Critical Infrastructure

    • Ayodeji James Akande, Ernest Foo, Zhe Hou, Qinyi Li
    Pages 1-22

  3. Blockchain in Smart Grids: A Review of Recent Developments

    • Teng Yu, Fengji Luo, Quanwang Wu, Gianluca Ranzi
    Pages 23-59

  4. Client Selection Frameworks Within Federated Machine Learning: The Current Paradigm

    • Lincoln Best, Ernest Foo, Hui Tian, Zahra Jadidi
    Pages 61-83

  5. Explainable Anomaly Detection in IoT Networks

    • Zahra Jadidi, Shantanu Pal
    Pages 85-94

  6. Application of Machine Learning on Material Science and Problem Solving Under Security—A Review

    • Maedeh Beheshti, Jolon Faichney
    Pages 95-117

  7. Introduction to Blockchain Technology with Bitcoin Protocol

    • Babu Pillai, Jeyakumar Samantha Tharani, Zhé Hóu, Kamanashis Biswas, Vallipuram Muthukkumarasamy
    Pages 119-137

  8. Security Challenges and Wireless Technology Choices in IoT-Based Smart Grids

    • Luke Kane, Vicky Liu, Matthew McKague, Geoffrey Walker
    Pages 139-167
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Editors and Affiliations

  • School of Information Technology, Deakin University, Burwood, Australia

    Shantanu Pal

  • School of Information and Comm Tech, Griffith University, Nathan, Australia

    Zahra Jadidi, Ernest Foo

  • School of Engineering, Macquarie University, Sydney, Australia

    Subhas C. Mukhopadhyay

Bibliographic Information

  • Book Title: Emerging Smart Technologies for Critical Infrastructure

  • Editors: Shantanu Pal, Zahra Jadidi, Ernest Foo, Subhas C. Mukhopadhyay

  • Series Title: Smart Sensors, Measurement and Instrumentation

  • DOI: https://doi.org/10.1007/978-3-031-29845-5

  • Publisher: Springer Cham

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023

  • Hardcover ISBN: 978-3-031-29844-8Published: 02 August 2023

  • Softcover ISBN: 978-3-031-29847-9Due: 03 July 2023

  • eBook ISBN: 978-3-031-29845-5Published: 01 June 2023

  • Series ISSN: 2194-8402

  • Series E-ISSN: 2194-8410

  • Edition Number: 1

  • Number of Pages: IX, 167

  • Number of Illustrations: 27 b/w illustrations, 24 illustrations in colour

  • Topics: Cyber-physical systems, IoT, Professional Computing, Machine Learning, Materials Science, general, Data Engineering

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