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JCSIS

Data Mining for Renewable Energy Efficiency Optimization in Smart Cities and IoT Applications

Khadija ShazlyHakan KhanNajaad OubeBlika
Volume 4

Abstract

Efficient management of renewable energy resources is vital for the sustainability of smart cities. This research introduces a data mining-driven approach to optimize energy efficiency across smart city infrastructures integrated with IoT applications. Large-scale data from smart grids, sensor networks, and urban energy consumption patterns are analyzed using classification, clustering, and association rule mining techniques to uncover hidden patterns and predict energy demands. The integration of data mining with real-time IoT inputs facilitates dynamic load balancing, peak demand prediction, and intelligent distribution of renewable energy sources such as solar and wind. Experimental validation demonstrates that the proposed framework significantly enhances system responsiveness, reduces energy waste, and supports strategic decision-making for sustainable urban energy ecosystems.

Keywords

Data mining, renewable energy, smart cities, IoT applications, energy efficiency, intelligent systems

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