This study explores energy-efficient routing methods in smart water distribution networks using the Ant Colony Optimization (ACO) algorithm. With the growing need for optimal water resource management in smart cities, the use of metaheuristic algorithms for improving energy efficiency has gained significance. In this research, an ACO-based routing model is proposed to minimize energy consumption in water distribution systems. Through various simulations, the performance of this approach is evaluated in comparison to traditional methods. The results indicate that the proposed approach reduces energy consumption, enhances network reliability, and optimizes water distribution routes. The simulation results demonstrate that the ACO-based routing strategy significantly reduces energy consumption while maintaining stable pressure and flow conditions, indicating its effectiveness for energy-aware operation of smart water distribution networks. Future studies may focus on integrating real-time IoT sensor data and multi-objective optimization criteria into the ACO framework to further enhance scalability and adaptability in large-scale smart water networks.