Application of AI in Optimizing Energy and Resource Management: Effectiveness of Deep Learning Models

Agus Kristian (Muhammadiyah University of Tangerang)
Thomas Sumarsan Goh (Indonesian Methodist University)
Ahmad Ramadan (University of Raharja)
Archa Erica (Adi Journal Incorporation)
Sondang Visiana Sihotang (Association of Indonesian Private Universities)

International Transactions on Artificial Intelligence (ITALIC)
Vol. 2 No. 2 (2024): International Transactions on Artificial Intelligence

In the era of globalization and rapid industrial growth, energy efficiency and resource management are crucial to addressing complex environmental and economic challenges. Efficient management reduces costs and contributes to sustainability. Technological advancements in Artificial Intelligence (AI) enhance energy efficiency and resource management through faster data analysis, better predictions, and automation. Despite progress, challenges like inaccurate energy demand predictions and inefficient resource allocation persist. This study explores AI's role in improving energy and resource management efficiency, focusing on prediction, optimization, and automation using Deep Learning approaches, including Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks. The findings show that AI models significantly enhance efficiency and sustainability by providing accurate predictions and automation recommendations. This research underscores AI's practical relevance, suggesting companies integrate these technologies to optimize energy use and achieve sustainability goals.