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Energy-Efficient Algorithms for Image Processing on Edge Devices

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  • Sumana Chakraborty
Sumana Chakraborty
Assistant Professor, Dept. of CSE(Swami Vivekananda University)

Published 2025-12-22

Keywords

  • energy-efficient algorithms,
  • edge devices,
  • image processing,
  • low-power computing,
  • deep learning,
  • model compression,
  • Internet of Things (IoT),
  • edge AI,
  • optimization,
  • real-time processing
    • ...More
    Less

How to Cite

Chakraborty, Sumana. “Energy-Efficient Algorithms for Image Processing on Edge Devices”. Swami Vivekananda University Press, Dec. 2025, pp. 109-14, https://swamivivekanandauniversitypress.com/index.php/svup/article/view/217.

Copyright (c) 2025 Swami Vivekananda University Press

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Abstract

As edge devices such as smartphones, IoT devices, and wearable technologies proliferate, there is an increasing need for energy-efficient algorithms to perform image processing tasks locally. This paper explores the development of energy-efficient image processing algorithms designed for edge devices, focusing on real-time tasks like object detection, segmentation, and recognition. We review techniques such as model compression, quantization, pruning, and adaptive neural networks that enable efficient computation with constrained resources. Additionally, we investigate the trade-offs between energy efficiency, accuracy, and speed in image processing tasks on edge platforms. The integration of deep learning models in edge computing environments, along with their implications for sustainable and eco-friendly computing, is also discussed.

DOI - https://doi.org/10.65525/SVUP.9788199565463.2026.109-114

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