Big Data Challenges for the Internet of Things (IoT) Paradigm
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 senso...
| Main Authors: | , , , |
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| Format: | Book Chapter |
| Published: |
Springer International Publishing
2017
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| Online Access: | https://doi.org/10.1007/978-3-319-70102-8_3 http://hdl.handle.net/20.500.11937/69158 |
| Summary: | 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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