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2024 | OriginalPaper | Buchkapitel

5. Exploring IoT Communication Technologies and Data-Driven Solutions

verfasst von : Poonam Maurya, Abhishek Hazra, Lalit Kumar Awasthi

Erschienen in: Learning Techniques for the Internet of Things

Verlag: Springer Nature Switzerland

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Abstract

Over the past decade, Internet of Things (IoT) networks have been the subject of active research due to their wide range of potential applications. The successful implementation and effective performance of IoT networks depend on the communication protocols used to connect spatially distributed devices or sensors. However, existing communication technologies face several challenges, including security, interoperability, scalability, and energy optimization. Therefore, researchers are currently exploring novel IoT communication protocols and embracing data-driven approaches along with other solutions to overcome these challenges. This chapter comprehensively explores emerging trends in IoT communication technologies and the integration of data-driven solutions. Additionally, we study the potential role of data-driven technologies, such as artificial intelligence (AI), machine learning (ML), and deep learning (DL), focusing on their integration with IoT technologies. We have also briefly discussed the benefits of using data-driven technologies in various IoT applications. Furthermore, we have outlined several potential challenges and how data-driven technologies can address them, emphasizing recent innovations.

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Titel: Exploring IoT Communication Technologies and Data-Driven Solutions
verfasst von: Poonam Maurya
Abhishek Hazra
Lalit Kumar Awasthi
Verlag: Springer Nature Switzerland
Buch: Learning Techniques for the Internet of Things
Print ISBN: 978-3-031-50513-3

Electronic ISBN: 978-3-031-50514-0

Copyright-Jahr: 2024
DOI: https://doi.org/10.1007/978-3-031-50514-0_5

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