IoT Generated Big Data Analytics: Trends and Scalability Issues

Authors

  • Hassan Raza Washington University of science and technology, USA Author
  • Tsendayush Erdenetsogt University of the Potomac, USA Author
  • Muhammad Mohsin Kabeer Gannon University, USA Author
  • Muhammad Shahrukh Aslam Washington University of science and technology, USA Author

Keywords:

IoT, Big data analytics, scalability, edge computing, cloud computing, machine learning

Abstract

The high rate at which Internet of Things (IoT) devices are being created has resulted in the creation of large, heterogeneous, and fast datasets, which form the IoT-generated Big Data. The effective processing of such data is essential to allow making intelligent decisions, making predictions, and automation in various areas of application including smart cities, healthcare, industrial solutions, and transportation. The current trends, architectures and analytics methods used in IoT Big Data systems are discussed in this review with a specific emphasis on the scalability issue, security considerations and strategies of managing data. Also, the latest technologies like edge computing, AI-based analytics, digital twins and blockchain are addressed. The paper outlines the open research issues and prospects, providing an overall insight to the creation of scalable, secure, and intelligent IoT analytics systems.

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Published

2026-03-09

Issue

Vol. 1 No. 2 (2025): Advancements in AI and computing

Section

Articles