Abstract Machine learning is one of the emerging technologies that has grabbed the attention of academicians and industrialists, and is expected to evolve in the near future. Machine learning techniques are anticipated to provide pervasive connections for wireless nodes. In fact, machine learning paves the way for the Internet of Things (IoT)—a network that supports communications among various devices without human interactions. Machine learning techniques are being utilized in several fields such as healthcare, smart grids, vehicular communications, and so on. In this paper, we study different IoT-based machine learning mechanisms that are used in the mentioned fields among others. In addition, the lessons learned are reported and the assessments are explored viewing the basic aim machine learning techniques are expected to play in IoT networks.
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Machine learning in the Internet of Things: Designed techniques for smart cities
Semantic Scholar · Computer Science · 2019
Abstract
Abstract Machine learning is one of the emerging technologies that has grabbed the attention of academicians and industrialists, and is expected to evolve in the near future. Machine learning techniques are anticipated to provide pervasive connections for wireless nodes. In fact, machine learning paves the way for the Internet of Things (IoT)—a network that supports communications among various devices without human interactions. Machine learning techniques are being utilized in several fields such as healthcare, smart grids, vehicular communications, and so on. In this paper, we study different IoT-based machine learning mechanisms that are used in the mentioned fields among others. In addition, the lessons learned are reported and the assessments are explored viewing the basic aim machine learning techniques are expected to play in IoT networks.