This section comprehensively addresses the concepts of the Internet of Things (IoT) and Artificial Intelligence of Things (AIoT), their fundamental components, architectural approaches, and primary use cases within an integrated framework. IoT is defined as an ecosystem that collects data from the physical world through sensors and network infrastructure, transmits this data, and converts it into services at the application layer; its contributions in areas such as smart homes, healthcare, agriculture, environmental monitoring, transportation, smart cities, and industry are highlighted. It is explained that IoT has evolved into AIoT by integrating with artificial intelligence due to the rapidly increasing data production and the need for real-time decisions. It is noted that AIoT offers a structure that not only transmits data but also analyses it and produces local-level inferences; however, this also brings challenges such as computational load, storage requirements, and data security. A three-tiered approach is fundamental to the architecture of IoT, and the role of cloud computing and edge computing is discussed in the context of latency, bandwidth, and performance requirements. In the AIoT architecture, a layered structure extending from the edge-cloud level to the cloud is explained. Cloud-based and edge-cloud collaboration-based paradigms are compared. Finally, it is noted that AIoT today contributes to enhancing predictive, adaptive, and optimisation capabilities beyond automation, while also serving as an application domain for new approaches such as TinyML, federated learning, digital twins, and edge image processing.