Energy consumption in the industrial sector accounts for a substantial share of global energy usage, leading to increasing interest in solutions that can optimize efficiency and reduce operational costs. Advances in the Internet of Things (IoT) and Artificial Intelligence (AI), including Machine Learning (ML), offer powerful ways to monitor industrial systems, perform predictive analytics, and integrate renewable resources into manufacturing and power distribution processes. This paper reviews the state-of-the-art in AI and IoT for energy conservation within industrial settings. It discusses key applications such as real-time monitoring and control, AI-based optimization, predictive maintenance, and energy theft detection. The review concludes by highlighting challenges, including data heterogeneity and scalability, and proposes future directions such as federated learning, quantum-enhanced optimization, and robust ethical frameworks.
Sehgal et al. (2025) studied this question.
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