AI-Enhanced Thermal Performance and Energy Efficiency in Tropical Buildings: A Case Study of Advanced Glass and Aluminum Composite Panels

In tropical climates, maintaining energy efficiency and thermal comfort is challenging due to high solar exposure and humidity. This study, conducted at the Central Laboratory Building, Diponegoro University, Indonesia, evaluates Aluminum Composite Panels (ACP) and high-performance glass. The research uses IoT-enabled real-time monitoring, AI-driven sensitivity analysis, and state-of-the-art simulations. Key findings show ACP with ventilated air cavities reduces indoor temperatures by up to 4.5°C and achieves a 28% energy savings, outperforming traditional brick walls and glass-only facades. Thermal resistance improved by 60%, and the Solar Heat Gain Coefficient (SHGC) was reduced by 20% with reflective coatings. AI-powered models identified the optimal ACP configuration with a 50mm air cavity and northwest orientation for the best thermal performance and energy efficiency. The study integrates real-world data with simulations, offering actionable insights into sustainable building design. It highlights the potential of climate-adaptive facades and predictive AI tools to address future climate scenarios, projecting an additional 35% energy savings under extreme conditions. This research contributes to global sustainability, providing a framework for architects, urban planners, and policymakers to create energy-efficient architecture in tropical regions.