The integration of the Internet of Things (IoT) with edge computing has emerged as a crucial research area aimed at reducing latency, improving scalability, and enabling real-time data processing in distributed IoT networks. Research papers in this domain explore architectures and frameworks that bring computation, storage, and intelligence closer to IoT devices, supporting applications such as smart cities, autonomous vehicles, industrial automation, healthcare, and environmental monitoring. Key contributions include edge-assisted data analytics, lightweight machine learning, resource allocation strategies, and security and privacy mechanisms tailored for constrained IoT devices. Recent studies also address challenges like heterogeneity of devices, dynamic workload management, energy efficiency, and integration with cloud and fog computing. By leveraging AI, federated learning, and zero trust architectures at the edge, IoT-edge computing research is driving the development of intelligent, resilient, and low-latency IoT ecosystems.