Enhancing the Energy Efficiency of Wireless Sensor Networks in IoT

The core foundation of Internet of Things (IoT) systems are wireless sensor networks (WSNs). Energy limitations provide a significant problem for the wireless nodes in these networks that are in charge of sensing. The complexity results from the challenging task of recharging or replacing the batteries of these nodes, a task frequently met with great difficulty. The energy problem is made worse by the fact that many real-world IoT situations involve dynamic sensing components that are in motion. In light of these worries, the current research is carefully designed to solve the real-world difficulties posed by WSNs that include mobile sensing components. The main goal is to use concept of radio-frequency (RF) energy extraction to alleviate energy restrictions that are inherent in such settings. With a framework designed to handle mobile sensing components capable of RF energy harvesting, proposed technique presents a novel procedure for the election of cluster heads (CH) within WSNs. This method holds great potential for overcoming the persistent energy puzzles that have repeatedly hampered the smooth operation of such networks. This method's key strength is its capacity to harness RF energy, which renews the nodes' power sources and increases their operational lives. The effectiveness of the suggested strategy is exposed through thorough simulations, which puts it favorably in contrast to current methodologies. The parameters of residual energy, count of functioning nodes, and overall network longevity all highlight this approach's superior performance and highlight its potential to change the WSN landscape within the dynamic and energy-conscious IoT environment.