Development of an Improved Wildfire Monitoring Scheme Based on an Energy-Efficient Clustering Approach for Flying Adhoc Network

S. C. Gasin, M. J. Musa, K. A. Abubilal, E. E. Agbon

Abstract


Wildfires pose significant threats to ecosystems, human lives, and infrastructure. Wireless Sensor Networks (WSNs) are widely used for applications like wildfire monitoring, but one of their limitations is energy consumption. Flying Ad Hoc Networks (FANETs) are a type of WSN that uses Unmanned Aerial Vehicles (UAVs) for communication with each other in a self-organized manner. Several clustering algorithms have been proposed for WSNs such as Low-Energy Adaptive Clustering Hierarchy (LEACH), LEACH with Cluster-head Election Control (LEACH-C), Particle Swarm Optimization-based Hierarchical Adaptive Sink (PSO-HAS), Sensor Emulator for Dynamic Energy-efficient Clustering (SEED), Energy Efficient - Smart Sensor (EE-SS), to conserve energy in WSNs. However, these algorithms consumed energy in the cluster formation leading to network overhead and inefficient bandwidth utilisation. To address these challenges, this paper presents an Energy Efficient Wildfire Monitoring Scheme (EEWMS) to reduce energy consumption inefficient bandwidth utilization in cluster formation. It computes a appropriate cluster count before cluster formation. Simulation was carried out using MATLAD and result obtained showed that the EEWMS reduces energy consumption by 10.25% compared to EE-SS. In addition, EEWMS reduces cluster building time by 10.16%, to EE-SS. These results highlight EEWMS's potential for improving wildfire monitoring in FANETs.


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References


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