Intelligent Building Management: Leveraging AI and VAV for Sustainable HVAC Performance

Abstract

This review explores the integration of Artificial Intelligence (AI) driven Variable Air Volume (VAV) systems and Building Management Systems (BMS) to enhance thermal comfort and energy efficiency in commercial buildings. With HVAC systems accounting for up to 70 percent of energy use in Malaysian commercial sectors, improving their performance is both an economic and environmental imperative. The paper evaluates how intelligent BMS architectures comprising field devices, automation controls, and centralized management layers enable real-time data driven optimization of indoor climate. Special emphasis is placed on the role of VAV systems in enabling zone-specific climate regulation and reducing energy waste. National initiatives such as MS 1525:2019, the Energy Efficiency and Conservation Act 2024, and the National Energy Transition Roadmap (NETR) are examined to contextualize Malaysia’s policy framework for sustainable building practices. Despite technical and financial barriers such as outdated infrastructure, high retrofitting costs, and control complexity, the convergence of IoT technologies and AI based predictive control shows strong potential to overcome these limitations. This review highlights critical pathways for future research and industry adoption toward more resilient, efficient, and occupant centric building environments.