A Review of Data Mining Techniques for Enhancing Energy Efficiency in IoT Systems

Abstract

The rapid proliferation of Internet of Things (IoT) technologies has led to an unprecedented surge in data generation and energy consumption, raising concerns about sustainability and operational efficiency. This review explores the role of data mining techniques in enhancing energy efficiency across various IoT applications. By analyzing and classifying key data mining methods such as clustering, classification, association rule mining, and anomaly detection this paper highlights how intelligent data processing can optimize energy usage in IoT networks, reduce resource wastage, and prolong device lifespan. The review further discusses real-world case studies, emerging trends, and challenges in integrating data mining with energy-aware IoT systems. It concludes by identifying potential research directions aimed at building smarter, greener, and more sustainable IoT infrastructures.