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<p>Smart environmental monitoring in urban areas demands highly efficient sensor networks capable of minimizing energy consumption while maintaining reliable 5G connectivity. This paper proposes a novel three-layer framework for energy-efficient 5G-enabled sensor networks tailored for sustainable cities. The <i>Glass Sponge Topology Layer</i> reduces signaling overhead and coverage redundancy by implementing a lightweight, lattice-inspired sensor deployment. The <i>Electric Eel Energy Layer</i> makes energy storage and transmission scheduling pulse-based to reduce idle energy consumption in the network. The <i>Ant Colony Routing Hybrid Layer</i> adaptively optimizes routing paths with pheromone-inspired scoring for low-latency and energy-efficient routing. Simulation tests on an urban deployment of 1&#xa0;km² sensors demonstrate that the framework saves 32% of total network energy consumption, decreases average latency from 18 ms to 11 ms, and reduces redundant overlap of area coverage by 28% over regular grid and random topologies. These outcomes clearly indicate the framework’s ability to make urban environmental monitoring networks significantly more sustainable and efficient.</p>

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Energy-efficient 5G-enabled sensor networks for smart environmental monitoring in sustainable cities

  • 期刊论文

  • 发表日期：

    2026年1月17日

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  • Issam Trrad,
  • Rabah Ismail,
  • Hashem Al-Mattarneh,
  • Snehal Hole

摘要

Smart environmental monitoring in urban areas demands highly efficient sensor networks capable of minimizing energy consumption while maintaining reliable 5G connectivity. This paper proposes a novel three-layer framework for energy-efficient 5G-enabled sensor networks tailored for sustainable cities. The Glass Sponge Topology Layer reduces signaling overhead and coverage redundancy by implementing a lightweight, lattice-inspired sensor deployment. The Electric Eel Energy Layer makes energy storage and transmission scheduling pulse-based to reduce idle energy consumption in the network. The Ant Colony Routing Hybrid Layer adaptively optimizes routing paths with pheromone-inspired scoring for low-latency and energy-efficient routing. Simulation tests on an urban deployment of 1 km² sensors demonstrate that the framework saves 32% of total network energy consumption, decreases average latency from 18 ms to 11 ms, and reduces redundant overlap of area coverage by 28% over regular grid and random topologies. These outcomes clearly indicate the framework’s ability to make urban environmental monitoring networks significantly more sustainable and efficient.