Smart Irrigation Enhancement Through UAV-Based Clustering and Wireless Charging in Wireless Sensor Networks

Wireless sensor networks (WSNs) enable large-scale data collection across wide areas but face significant challenges, including limited energy resources, unbalanced energy consumption, and inefficient data transmission, leading to reduced network lifetime and poor reliability. To address these issues, this paper proposes an energy-efficient clustering scheme that integrates unmanned aerial vehicle (UAV)-assisted data collection and wireless power transfer (WPT) to enhance WSN performance in smart irrigation applications. The proposed scheme divides the network into two regions: a central circular area containing standard nodes and an outer region divided into four clusters housing advanced nodes. It dynamically adjusts cluster formation, optimizes cluster head (CH) selection based on residual energy, minimizes transmission hops, and ensures the shortest possible UAV path, thereby reducing energy consumption. Additionally, UAV-based WPT provides continuous energy replenishment, mitigating the hotspot problem and extending network lifetime. Extensive simulations demonstrate that the proposed scheme reduces energy consumption by up to 13.16%, enhances data collection efficiency by 8.84%, and extends network lifetime by more than 9.6% compared to Yoon’s scheme. Additionally, the proposed scheme achieves 26% higher residual energy and a 43% increase in throughput over Yoon’s scheme. Moreover, in smart irrigation applications, the proposed scheme reduces water consumption by approximately 20%, demonstrating its effectiveness for sustainable precision agriculture.