Edge Computing for Real-Time Data Processing in IoT Sensor Networks

Abstract

By enabling connectivity between devices, sensors, and systems and enabling real-time decision-making, the Internet of Things (IoT) has drastically changed several industries. However, there are issues with latency, bandwidth usage, and data processing efficiency due to the massive amount of data produced by IoT devices. By enabling real-time data processing at the network's edge and lowering dependency on centralized cloud services, edge computing which moves computation and storage closer to the data source offers a viable answer to these problems. This paper explores the role of edge computing in enhancing the performance of IoT sensor networks by addressing issues such as latency, bandwidth optimization, and real-time data analysis. Many industries have seen significant change due to the Internet of Things (IoT), which enables connectivity between devices, sensors, and systems and real-time decision-making. However, because of the enormous volume of data generated by IoT devices, there are problems with latency, bandwidth consumption, and data processing efficiency. Edge computing, which shifts computation and storage closer to the data source, provides a workable solution to these issues by enabling real-time data processing at the network's edge and reducing reliance on centralized cloud services.