The Internet of Things (IoT) has been a major significant trend in recent years, and it is the explosive growth of devices connected and controlled by the Internet. It has been widely used and is an integral part of people’s lives where it has been applied in almost all fields including home, building automation, customer market, healthcare, education, transportation, agriculture, and others. However, various serious challenges and limitations in the growth of IoT need to be solved. Thus, Artificial Intelligence (AI) has been applied to reduce IoT issues and optimize its challenges. One of the main AI solutions used in IoT is Swarm Intelligence (SI) where natural biological algorithms are used the inspire natural beings like bird flocking, ant colonies, hawks hunting, bacterial growth, animal herding, fish schooling, and microbial intelligence. This paper discusses an overview of the Internet of Things and reports a brief aspects of SI algorithms and and how they are adapted to enhance some IoT challenges. This review will guide future studies, giving a clearer way to help determine the suitable SI-based algorithm for IoT-based systems.