Edge Computing for Energy Efficiency in Smart City IoT Deployments

Authors

https://doi.org/10.48314/ceti.vi.53

Abstract

The rapid growth of Internet of Things (IoT) technologies in smart city infrastructures has revolutionized urban management systems. However, the increasing number of IoT devices leads to significant energy consumption, creating a need for more efficient approaches to data processing and transmission. Traditional cloud-based IoT frameworks often result in high latency and energy inefficiencies due to the centralization of data processing, which requires extensive data transmission to and from cloud servers. Edge computing emerges as a solution by processing data closer to the source, reducing the reliance on centralized cloud systems and minimizing energy consumption and network bandwidth. This paper explores how edge computing can be applied to enhance energy efficiency in smart city IoT deployments. By shifting computational tasks from the cloud to edge devices, such as routers and gateways, we can significantly reduce the energy overhead associated with long-distance data transmission and central processing. The research presents a comparative analysis of energy consumption in conventional cloud-based IoT models versus edge computing-based systems. Additionally, the paper introduces a novel energy optimization framework that leverages edge computing architecture to dynamically adjust computational loads based on real-time energy metrics and network conditions. Results from the simulation experiments demonstrate a substantial reduction in overall energy consumption and latency in edge computing-based smart city deployments compared to traditional cloud-based models. The findings suggest that integrating edge computing into smart city infrastructures not only enhances energy efficiency but also improves data security and processing speed, making it a more sustainable and scalable solution for future smart cities. These results have significant implications for policymakers and urban planners looking to implement energy-efficient, data-driven smart city initiatives.

Keywords:

Edge computing, Energy efficiency, Smart city, IoT deployments, Smart infrastructure this abstract provides a clear, Concise summary of the problem, Methods, Implications for the study of edge computing in smart cities

References

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Published

2025-02-15

Issue

Vol. 2 No. 1 (2025): Computational Engineering and Technology Innovations

Section

Articles

How to Cite

Ghasemabadi, N., & Hami Hassan Kiyadeh, S. (2025). Edge Computing for Energy Efficiency in Smart City IoT Deployments. Computational Engineering and Technology Innovations, 2(1), 34-44. https://doi.org/10.48314/ceti.vi.53

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