A Study on Energy Efficient Routing in Smart Water Distribution Network Using the ACO

In the context of evolving urban infrastructure, efficient water resource management has become imperative, particularly within smart city ecosystems. This study explores the integration of the Ant Colony Optimization (ACO) algorithm to improve energy efficiency in smart water distribution networks. By simulating the routing paths through ACO, the proposed method optimizes water flow, minimizes energy consumption, and maintains service reliability. A comparative analysis against traditional routing algorithms demonstrates the superior performance of ACO in terms of computational efficiency and energy savings. The study also includes a simulation with a Python-based implementation of ACO, Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) on a 3D sensor network. The results confirm the potential of ACO as a scalable, intelligent solution to future challenges in urban water distribution. This research also highlights the adaptability of ACO in real-time applications, promoting its integration into smart grid infrastructure and IoT-based water management systems.