Current Efficacy and Innovations in Smart Home Energy Management: A Review of IoT, AI, and Renewable Integration for Optimal Efficiency

Articles in Press

Document Type : Review paper

Author

Department of Energy, Hanze University of Applied Science, Groningen, Netherland.

Abstract

Smart home energy management (SHEM) strategies effectively overcome the limitations of traditional methods by automating tasks through smart meters, appliances, and home automation systems, thus reducing manual effort and enhancing efficiency. Using Internet of Things (IoT) and artificial intelligence (AI) technologies, SHEM systems provide real-time optimization and precise adjustments, leading to quick identification and reduction of energy waste. They facilitate the integration and optimization of renewable energy sources like solar panels, improving sustainability and reducing reliance on grid electricity. Additionally, SHEM systems are scalable, accommodating the needs of larger or more complex homes while offering significant energy savings and enhanced convenience. Recent advancements include integrating advanced metering infrastructure, smart sensors, and home energy storage systems with supervisory control and data acquisition (SCADA) to manage energy generation, transmission, and distribution effectively. Despite the potential benefits, challenges remain, such as system complexity and the need for optimal control strategies. Thus, continued research and development are crucial for refining smart solutions and algorithms, ultimately enhancing energy efficiency, cost savings, and user comfort. The evolving role of smart homes and grids underscores the importance of collaboration among researchers, industry stakeholders, and policymakers to achieve a more sustainable, efficient, and secure future. This review explores SHEM systems, highlighting recent studies using advanced technologies like smart meters, IoT, AI, and other tools to improve energy efficiency, reduce costs, and integrate renewable energy, while addressing challenges.

Keywords

Main Subjects

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Journal of Operation and Automation in Power Engineering

Articles in Press, Corrected Proof
Available Online from 09 May 2026

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  • Receive Date: 17 February 2025
  • Revise Date: 30 August 2025
  • Accept Date: 10 September 2025
  • First Publish Date: 09 May 2026

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