Semantic Scholar Open Access 2020 209 sitasi

Machine learning and data analytics for the IoT

Erwin Adi A. Anwar Zubair A. Baig S. Zeadally

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Abstrak

The Internet of Things (IoT) applications have grown in exorbitant numbers, generating a large amount of data required for intelligent data processing. However, the varying IoT infrastructures (i.e., cloud, edge, fog) and the limitations of the IoT application layer protocols in transmitting/receiving messages become the barriers in creating intelligent IoT applications. These barriers prevent current intelligent IoT applications to adaptively learn from other IoT applications. In this paper, we critically review how IoT-generated data are processed for machine learning analysis and highlight the current challenges in furthering intelligent solutions in the IoT environment. Furthermore, we propose a framework to enable IoT applications to adaptively learn from other IoT applications and present a case study in how the framework can be applied to the real studies in the literature. Finally, we discuss the key factors that have an impact on future intelligent applications for the IoT.

Topik & Kata Kunci

Computer Science Engineering

Penulis (4)

Erwin Adi

A. Anwar

Zubair A. Baig

S. Zeadally

Format Sitasi

APA MLA BibTeX

Adi, E., Anwar, A., Baig, Z.A., Zeadally, S. (2020). Machine learning and data analytics for the IoT. https://doi.org/10.1007/s00521-020-04874-y

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Lihat di Sumber doi.org/10.1007/s00521-020-04874-y

Informasi Jurnal

Tahun Terbit: 2020
Bahasa: en
Total Sitasi: 209×
Sumber Database: Semantic Scholar
DOI: 10.1007/s00521-020-04874-y
Akses: Open Access ✓