Energy Efficient Data Transmission In Wireless Sensor Networks For Agriculture Datasets

Abstract

Wireless sensor networks (WSNs) play a vital role in data collection and monitoring in agriculture applications. However, energy efficiency is a critical concern in WSNs due to the limited power resources of sensor nodes. This paper proposes an energy-efficient data transmission approach for WSNs in agriculture datasets by integrating two metaheuristic optimization algorithms, namely Particle Swarm Optimization (PSO) and Improved Grey Wolf Optimization (I-GWO) The PSO algorithm is utilized to optimize the clustering process in WSNs, aiming to minimize energy consumption and prolong network lifetime. I-GWO algorithm is then employed to optimize the routing path within each cluster, considering factors such as residual energy and distance. By combining these two algorithms, the proposed approach achieves efficient utilization of energy resources while ensuring reliable data transmission in agriculture WSNs. Extensive simulations are conducted to evaluate the performance of the proposed approach, and the results demonstrate its superiority in terms of energy efficiency and data transmission reliability.