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Preface
Part I: Chapter 1 introduces the Internet of Things with several definitions and
discusses the benefits and challenges of establishing the IoT. It reviews IoT reference
models, state-of-the-art IoT platforms, and the applications of IoT in vertical
markets. In addition, this chapter helps you make sense of the business-related
aspects of IoT technology. Chapter 2 addresses “IoT/devices” and its fundamental
building blocks including microcontrollers, interfaces, sensors, and actuators. In
Chap. 3, the details of networking technologies and protocols are covered. Chapter 4
looks into IoT cloud covering the fundamentals of cloud computing, data ingestion,
data processing, data storage, and data visualization. Chapter 5 addresses topics
relating to machine learning techniques such as regression, classification, clustering,
deep learning, and convolutional neural network. Chapter 6 is a definitive guide to
the Hadoop ecosystem. Chapter 7 is an introductory text on cyber-physical systems
in the IoT era. Distributed ledger technologies (DLT) and blockchain for IoT are
presented in Chap. 8. Emerging hardware technology for processing IoT data at the
edge or in the cloud including alternative computing, approximate computing, and
in-memory computing is discussed in Chap. 9. Finally, end-to-end IoT security is
covered in Chap. 10.
Part II: The second part of this book consists of three chapters. Chapter 11
addresses all important aspects of IoT technologies for smart healthcare: wearable
sensors, body area sensors, advanced pervasive healthcare systems, and big data
analytics. Chapter 12 covers biomedical engineering fundamentals to enable the
building of wearable healthcare devices or to understand biomedical data easily.
Finally, Chap. 13 provides a snapshot of the state-of-the-art research in data-driven
e-Health studies that leverage artificial intelligence technologies for making sense
of personal health data, as well as for delivering situational, actionable insights in
care flows.
Durham, USA
Farshad Firouzi
Durham, USA
Krishnendu Chakrabarty
Austin, USA
Sani Nassif
Preface
Part I: Chapter 1 introduces the Internet of Things with several definitions and
discusses the benefits and challenges of establishing the IoT. It reviews IoT reference
models, state-of-the-art IoT platforms, and the applications of IoT in vertical
markets. In addition, this chapter helps you make sense of the business-related
aspects of IoT technology. Chapter 2 addresses “IoT/devices” and its fundamental
building blocks including microcontrollers, interfaces, sensors, and actuators. In
Chap. 3, the details of networking technologies and protocols are covered. Chapter 4
looks into IoT cloud covering the fundamentals of cloud computing, data ingestion,
data processing, data storage, and data visualization. Chapter 5 addresses topics
relating to machine learning techniques such as regression, classification, clustering,
deep learning, and convolutional neural network. Chapter 6 is a definitive guide to
the Hadoop ecosystem. Chapter 7 is an introductory text on cyber-physical systems
in the IoT era. Distributed ledger technologies (DLT) and blockchain for IoT are
presented in Chap. 8. Emerging hardware technology for processing IoT data at the
edge or in the cloud including alternative computing, approximate computing, and
in-memory computing is discussed in Chap. 9. Finally, end-to-end IoT security is
covered in Chap. 10.
Part II: The second part of this book consists of three chapters. Chapter 11
addresses all important aspects of IoT technologies for smart healthcare: wearable
sensors, body area sensors, advanced pervasive healthcare systems, and big data
analytics. Chapter 12 covers biomedical engineering fundamentals to enable the
building of wearable healthcare devices or to understand biomedical data easily.
Finally, Chap. 13 provides a snapshot of the state-of-the-art research in data-driven
e-Health studies that leverage artificial intelligence technologies for making sense
of personal health data, as well as for delivering situational, actionable insights in
care flows.
Durham, USA
Farshad Firouzi
Durham, USA
Krishnendu Chakrabarty
Austin, USA
Sani Nassif