Urban Intelligent Structure Layout Based on Graph Neural Network and Multi-Objective Optimization

In the context of the ‘Internet of Everything’ in smart cities, the coordinated deployment of urban infrastructure and functional networks has become key to achieving efficient urban management. This study proposes an intelligent deployment method that combines graph neural networks (GNNs) with multi-objective particle swarm optimization (MOPSO) to optimize the deployment of urban smart facilities such as smart streetlights and underground pipe networks. This method combines urban infrastructure planning with advanced artificial intelligence and optimization techniques in an interdisciplinary approach, improving perception coverage, communication stability, and energy consumption balance in urban areas. Simulation experiments in a digital twin environment verify the feasibility and superiority of this method in the coordinated planning of smart city infrastructure, outperforming traditional deployment strategies.