IoT semantics is an important research domain that focuses on enhancing interoperability, data understanding, and intelligent decision-making in heterogeneous Internet of Things environments. Research papers in this area explore semantic models, ontologies, and knowledge representation techniques to give context and meaning to raw IoT data, enabling seamless integration across devices, platforms, and applications. Key contributions include semantic annotation of sensor data, ontology-based resource discovery, semantic middleware frameworks, and reasoning engines that support context-aware services. Recent works also investigate the role of AI, machine learning, and knowledge graphs in semantic data processing, along with blockchain and federated learning for secure and collaborative semantic IoT ecosystems. Challenges such as scalability, dynamic context adaptation, standardization, and real-time semantic interoperability remain open research issues. With the rise of smart cities, healthcare, industrial IoT, and autonomous systems, IoT semantics research continues to play a crucial role in enabling intelligent, interoperable, and future-ready IoT infrastructures.