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

    Access Status
    Fulltext not available
    Authors
    Wongthongtham, P.
    Kaur, J.
    Potdar, Vidyasagar
    Das, A.
    Date
    2017
    Type
    Book Chapter
    
    Metadata
    Show full item record
    Citation
    Wongthongtham, P. and Kaur, J. and Potdar, V. and Das, A. 2017. Big Data Challenges for the Internet of Things (IoT) Paradigm. In Connected Environments for the Internet of Things: Challenges and Solutions, 41-62. Switzerland: Springer International Publishing.
    Source Title
    Connected Environments for the Internet of Things: Challenges and Solutions
    DOI
    10.1007/978-3-319-70102-8_3
    Additional URLs
    https://doi.org/10.1007/978-3-319-70102-8_3
    ISBN
    978-3-319-70102-8
    School
    School of Management
    URI
    http://hdl.handle.net/20.500.11937/69158
    Collection
    • Curtin Research Publications
    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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