Abstract—Wireless Sensor Networks (WSNs) are crucial for data acquisition in various environments, but their performance is significantly limited by energy constraints. This paper introduces a novel method called Residual Battery, Communication Distance, and Mobility-Based Intelligent Clustering (RBCMIC) to improve network health and efficiency. The RBCMIC method selects optimal cluster heads by computing a fitness score based on remaining battery power, proximity to the Base Station (BS), and node mobility. This approach is compared with two existing methods Depth-Based Ratio (DBR) and Depth-Energy Aware Distribution (DEAD) in terms of energy efficiency, link overhead, and network lifetime. Simulation results show that RBCMIC significantly reduces energy consumption, enhances data delivery rates, and extends network lifetime.