This book presents a comprehensive exploration of LPWANs, delving into their fundamental concepts, underlying technologies, and the multifaceted challenges they tackle. This book recognizes that LPWANs don't operate in isolation; they are intimately intertwined with Artificial Intelligence and Machine Learning (AI/ML) technologies, which play a pivotal role in optimizing LPWAN performance and capabilities. The book is a collection of original contributions regarding air interface, transmission technologies and novel network architectures, such as network slicing, cloud/fog/edge computing, ad hoc networks and software-defined network. Also, this book provides a guide for researchers of IoT applications to choose suitable LPWAN technologies and describe the design aspects, network architectures, security issues and challenges. Features: Explains machine learning algorithms onto low-power wide area network sensors for compressed communications. Illustrates wireless-based Internet of Things networks using low-power wide area networks technology for quality air. Presents cognitive Internet of Things networks using wireless communication, and low-power wide area network technologies for Ad Hoc networks. Discusses a comprehensive study of low-power wide area networks for flying Ad Hoc networks. Showcases the study of energy efficient techniques aided by low-power wide area network technologies for the Internet of Things networks. The text is aimed at senior undergraduate, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.
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