ABSTRACT
The Internet of Things (IoT) is an emerging technology that has been widely used in a variety of fields, such as healthcare and medicine. Significant effort is being devoted to research, analysis, and innovative solutions related to high-density sensor networks used for the IoT concept. Machine learning (ML) plays a crucial role in enabling the extraction of hidden insights from vast amounts of data without an active search for patterns. ML is used for enhancing the security of IoT applications, tackling challenges, and facilitating profound analytics, leading to the development of effective smart IoT solutions. In this chapter, we present the application, security challenges, and techniques of ML and Low-Power Wide Area Networks (LPWAN) in the context of IoT. The results of this study indicate that, for the time being, LPWAN development will be based on widely accessible and well-proven ML techniques. Despite the considerable research advancements in current LPWAN and ML-based IoT technologies, several challenges remain unresolved and require further attention.
