Sustainable Development Goals and Energy Efficiency in Educational Institutions Through Smart Buildings and Machine Learning

Objective: This study aims to identify key characteristics of smart buildings that enhance sustainability and energy efficiency in educational institutions. By leveraging artificial intelligence, particularly machine learning, the study seeks to optimize energy consumption and improve learning environments. Theoretical Framework: Smart buildings integrate digital and communication technologies to enhance educational infrastructure. Despite their benefits, adoption in developing countries remains limited. This study builds on theories of sustainable energy management and computational optimization, emphasizing machine learning’s role in predictive energy modeling. Method: A machine learning model was developed to predict energy consumption in educational institutions. The k-nearest neighbor (k-NN) algorithm was applied using open-access data from the University of Durrës Building Energy Management System. Model validation was conducted through comparative analysis, assessing prediction accuracy and energy-saving potential. Results and Discussion: The model achieved an average relative error of 18.26%, confirming its predictive capability. Smart features enabled energy savings between 44.8% and 58.3%, depending on analyzed spaces. Additionally, an AI-powered interactive dashboard was proposed for real-time energy monitoring and optimization, aiding facility managers. Research Implications: This study underscores the role of smart buildings in promoting sustainability and reducing operational costs. AI-driven energy management systems can significantly enhance institutional sustainability practices. Originality/Value: This research demonstrates the effectiveness of machine learning in energy consumption prediction and proposes an AI-based solution for sustainable energy management in educational buildings. The findings provide valuable insights into integrating smart technologies for sustainability and efficiency.