Wireless Sensor Networks (WSNs) represent one of the most important research fields. Their performance can be affected by the issue of area coverage, as the sensor’s position is crucial in Wireless Sensor Networks (WSNs), particularly in high-risk environments. This paper presents a robust approach for sensor deployment in Wireless Sensor Networks (WSNs). The proposed approach utilizes Voronoi diagrams with the Pelican Optimization Algorithm (POA), employing effective objective functions to partition the area into as evenly partitioned areas as possible, thereby encouraging sensor coverage and balanced load distribution within each partition. The proposed methodology comprises two phases: the distributing phase and the grouping phase. POA is utilized in both phases to enhance sensor positions iteratively, thereby reducing gaps in coverage and achieving a balanced load distribution between regions and the sensors within each region. The simulation results demonstrate that the heuristic-driven deployment model significantly enhances coverage consistency and minimizes the variation of sensor distributions, proving its high performance in diverse configurations. A case study of Baghdad City illustrates the practical application of the proposed approach in environmental monitoring scenarios, such as tracking air pollution. This research develops WSN deployment methodologies, introducing an adaptable and scalable solution for achieving optimal resource allocation through optimal sensor coverage in real-world complex environments.