Optimized Clustering and Routing for Energy Efficiency in Smart Agricultural Wireless Sensor Networks

Innovative solutions for farming resource optimization, decision aid, and land monitoring are wireless sensor networks. Precision farming uses real-time field adjustments and crop health data to improve harvest efficiency. Spatially distributed WSNs (wireless sensor networks) will be used more in agriculture. Research has focused on en ergyefficiency techniques, which will become increasingly important as sensor nodes become more spread. Wireless communication may use plenty of energy. K-Medoid for clustering, Enhanced Artificial Bee Colony (EABC) for Adaptive Harris Hawk Optimization (AHHO) and cluster head selection for routing were developed for precision agriculture WSNs to save energy. Dispersed sensor nodes (DSN) This technique improves energy efficiency and network longevity works perfectly for dynamic agricultural and maximum-scale IoT deployments. Compared to CL-HPWSR, GCEEC, EW-DHOA, and LEACH, this algorithm is more reliable, scalable, and sustainable in smart agriculture applications. This improves farming efficiency and sustainability. Simulation results show that these methods achieves up to 23% lower energy consumption, 0.95 Mbps throughput (100 nodes), 98.7% packet delivery ratio, and 18$\mathbf{2 2 \%}$ longer network lifetime over existing approaches.