Optimization of energy efficiency in smart city IoT sensor networks
DOI:
https://doi.org/10.22105/sci.v2i1.29Keywords:
Energy efficiency, IoT sensor networks, Smart cities, Sustainability, Low-power protocols, Adaptive network topologies, Edge computingAbstract
As urban areas expand, smart city initiatives increasingly rely on IoT sensor networks to monitor and manage resources, optimize traffic, and enhance quality of life. However, these sensor networks face challenges in energy efficiency, which is critical to ensure long-term sustainability, reduce operational costs, and minimize environmental impact. This paper explores strategies to optimize energy efficiency within smart city IoT sensor networks, focusing on low-power protocols, adaptive network topologies, and efficient data transmission methods. This study identifies common energy bottlenecks by analyzing existing smart city implementations and evaluates emerging low-power technologies, such as Narrowband IoT (NB-IoT) and Long Range (LoRa) communication protocols. Further, it examines hardware improvements in sensor design and edge computing's role in reducing transmission energy by processing data closer to the source. Our analysis reveals that a hybrid approach—incorporating both hardware advancements and software optimization strategies—provides the most significant gains in energy efficiency. Additionally, we propose a framework that allows for adaptive power management based on environmental conditions and network demands, thereby enhancing the longevity and scalability of IoT networks in urban contexts. The findings from this study provide valuable insights for policymakers, urban planners, and technologists aiming to build sustainable smart cities, underscoring the importance of energy-aware designs in IoT infrastructure.
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