Tiago Rodrigues, Joana Morgado, Márcia Barros, Alan Oliveira, and José Cecílio, LASIGE Researchers, published the paper ” AI-driven IoT recommender system for enhancing energy efficient management in smart houses” in the Expert Systems with Applications journal, a Top-ranking journal.

This research presents the Artificial InTelligence-driven IoT REcommeNDEr Energy System (ATIRENDEE), a solution designed to enhance energy management in smart houses.

In recent years, the integration of solar power systems has seen substantial growth within smart houses. However, the inherent intermittency of solar irradiance introduces fluctuations in the available solar power, presenting a challenge for stable energy management. Developing and implementing precise recommendation systems based on solar power, energy market price, and weather forecasting methods become imperative in strategic planning and seamless energy management systems to address this issue effectively.

Leveraging deep learning algorithms, ATIRENDEE presents a novel stacked ensemble model designed to optimize energy consumption. Based on the obtained results, the ATIRENDEE approach can significantly reduce energy costs for smart homes, achieving an average monthly savings of over 45% and reaching up to 68% in specific cases. Its multi-layered recommendation approach enhances the efficiency and adaptability of the solution.

By dynamically optimizing energy allocation among solar, battery, and grid sources, ATIRENDEE consistently outperformed static grid-based approaches, promoting cost-effective and sustainable energy use in eco-friendly smart houses or buildings.

The paper is available here.