Energy Efficiency Improvement Methods for Edge AI IIoT Networks: An Overview
Yousef N. Shnaiwer, Julien Weber, Julien Roland, Megumi Kaneko, Robin Gerzaguet, Kenichi Kawamura, Olivier Berder, Salah Berra, Pascal Scalart, Keisuke Wakao, Yasushi Takatori · IEEE Internet of Things Magazine · 2025
The Industrial Internet of Things (IIoT) is transforming modern industries by enabling intelligent, data-driven operations at the edge of networks. As these systems grow in scale and complexity, optimizing the energy consumption of Machine Learning (ML) techniques becomes essential for sustainable and reliable performance. This article examines the architectural foundations of IIoT systems and offers a structured classification of methods for reducing the energy use of ML. A real-world case study, the Energy Efficient Internet of Emergency Services, illustrates the practical deployment of energy-optimized IIoT infrastructures in demanding operational contexts. The article concludes with a discussion of current challenges and future directions focused on ultra-low-power architectures, scalable deployment strategies, and robust security for next-generation industrial intelligence.