AI and IoT in Energy Conservation: Challenges, Opportunities, and Trends

The rapid advancements in Artificial Intelligence (AI) and the Internet of Things (IoT) have paved the way for innovative solutions to address global energy challenges. This paper explores the integration of AI and IoT in energy conservation, focusing on their combined potential to optimize energy consumption, enhance system efficiency, and support sustainable development. AI-driven predictive analytics and machine learning algorithms enable accurate energy demand forecasting and real-time decision-making, while IoT devices facilitate seamless data collection, monitoring, and control of energy systems. The synergy of these technologies has been instrumental in transforming energy management across various sectors, including smart grids, industrial automation, and smart buildings. However, their adoption comes with significant challenges, such as data security, interoperability, and the high cost of deployment. This review discusses the current state of AI and IoT in energy conservation, identifies key challenges, highlights emerging opportunities, and examines future trends, such as the role of blockchain and edge computing in decentralized energy systems. The paper concludes by emphasizing the need for interdisciplinary research and collaboration to unlock the full potential of AI and IoT in creating sustainable energy solutions.