Edge Computing-Based Real-Time Data Processing for Smart IoT Applications

Abstract

The rapid growth of IoT devices has generated large volumes of data that require efficient processing with minimal delay. Conventional cloud-centric architectures may introduce latency and communication overhead when real-time responses are required. This study investigates an edge computing framework for processing IoT data closer to the point of generation. The proposed architecture distributes computational tasks between IoT devices, edge nodes, and cloud infrastructure according to processing requirements and resource availability. Performance is evaluated using parameters such as response time, network traffic, computational efficiency, and energy consumption. By processing selected data locally, the proposed approach can reduce dependence on centralized cloud servers and improve the responsiveness of intelligent applications. The research demonstrates the potential of edge computing for applications such as smart cities, industrial monitoring, intelligent transportation, and healthcare IoT systems