Connectivity-Oriented Optimization of Scalable Wireless Sensor Topologies for Urban Smart Water Metering

Highlights: What are the main findings? A connectivity-oriented optimization model is proposed for the scalable deployment of wireless sensor networks in smart water metering. The model integrates georeferenced urban layouts, capacity-aware set-cover, and hybrid routing algorithms, reducing fragmentation and energy consumption. What are the implications of the main findings? Utilities can design resilient and cost-effective smart metering infrastructures while minimizing redundant infrastructure. The framework provides a scalable solution for smart cities, enabling sustainable urban water management and adaptive service planning. The growing need for efficient and sustainable urban water management has accelerated the adoption of smart monitoring infrastructures based on wireless sensor networks (WSNs). This study proposes a connectivity-aware methodology for the optimal deployment of wireless sensor networks (WSNs) in smart water metering systems. The approach models the wireless sensors as nodes embedded in household water meters and determines the minimal yet sufficient set of Data Aggregation Points required to ensure complete network coverage and transmission reliability. A scalable and hierarchical topology is generated by integrating an enhanced minimum spanning tree algorithm with set covering techniques and geographic constraints, leading to a robust intermediate layer of aggregation nodes. These nodes are wirelessly linked to a single cellular base station, minimizing infrastructure costs while preserving communication quality. Simulation results on realistic urban layouts demonstrate that the proposed strategy reduces network fragmentation, improves energy efficiency, and simplifies routing paths compared to traditional ad hoc designs. The results offer a practical framework for deploying resilient and cost-effective smart water metering solutions in densely populated urban environments.