<p>In dynamic and unpredictable situations, energy-constrained nodes in Wireless Sensor Networks (WSNs) must transmit data efficiently and last long. Traditional clustering and routing protocols frequently result in uneven energy depletion, redundant data transmissions, and suboptimal cluster formation. To address these limitations, we propose kSCM-PSO an energy efficient hybrid routing framework that integrates spatially-aware clustering and path optimization techniques using intelligent particles. As a clustering phase, we adopted the k-means algorithm to form spatially balanced clusters. An Adaptive Spatial Coverage Metric (A-SCM) it aids in the deterministically optimal selection of a Cluster Head (CH) inside each cluster and is based on node-centric factors including distance to the cluster centroid and node connection, covering an appreciably optimal area while maintaining equilibration of all nodes and the average energy status. During routing stage, a Particle Swarm Optimization (PSO) based algorithm is designed to setup energy efficient multi-hop paths from CHs to the sink, where the fitness function is a joint function of the ratio of Distance-Residual Energy (DRER) the link quality and the transmission cost. Based on simulation studies, the kSCM-PSO protocol has a greater energy efficiency, better lifetime and more reliable data delivery compared with others. Finally, this lightweight but flexible method presents a scalable approach for real-world WSN deployments that require spatial awareness and energy efficiency.</p>