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Big Data Challenges for the Internet of Things (IoT) Paradigm

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Connected Environments for the Internet of Things

Part of the book series: Computer Communications and Networks ((CCN))

Abstract

Millions of devices equipped with sensors are connected together to communicate with each other in order to collect and exchange data. The phenomenon of daily life objects that are interconnected through a worldwide network is known as the Internet of Things (IoT) or Internet of Objects. These sensors from a large number of devices or objects simultaneously and continuingly generate a huge amount of data, often referred to as Big Data. Handling this vast volume, and different varieties, of data imposes significant challenges when time, resources, and processing capabilities are constrained. Hence, Big Data analytics become even more challenging for data collected via the IoT. In this chapter, we discuss the challenges pertaining to Big Data in IoT; these challenges are associated with data management, data processing, unstructured data analytics, data visualization, interoperability, data semantics, scalability, data fusion, data integration, data quality, and data discovery. We present these challenges along with relevant solutions.

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Author information

Authors and Affiliations

  1. Curtin University, Perth, Australia

    Pornpit Wongthongtham, Jaswinder Kaur & Vidyasagar Potdar

  2. Tripura University (A Central University), Agartala, India

    Abhishek Das

Authors
  1. Pornpit Wongthongtham
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  2. Jaswinder Kaur
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  3. Vidyasagar Potdar
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  4. Abhishek Das
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Corresponding author

Correspondence to Pornpit Wongthongtham .

Editor information

Editors and Affiliations

  1. Debesis Education UK, University of Derby, Derby, United Kingdom

    Zaigham Mahmood

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Wongthongtham, P., Kaur, J., Potdar, V., Das, A. (2017). Big Data Challenges for the Internet of Things (IoT) Paradigm. In: Mahmood, Z. (eds) Connected Environments for the Internet of Things. Computer Communications and Networks. Springer, Cham. https://doi.org/10.1007/978-3-319-70102-8_3

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  • DOI: https://doi.org/10.1007/978-3-319-70102-8_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-70101-1

  • Online ISBN: 978-3-319-70102-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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