The building sector has long suffered from energy waste due to excessive cooling and inefficient lighting, which seriously impedes the realization of carbon neutrality goals. According to the United Nations Environment Programme, building operations account for 36% of global end-use energy consumption and emit up to 10 billion tons of CO annuallythree times the combined emissions of global aviation and shipping. In commercial buildings, 35% of air conditioning energy use stems from overcooling, while 22% of lighting energy is consumed in unoccupied areas. Against this backdrop, this study explores the application of intelligent energy-saving systems in smart buildings. It proposes an integrated system architecture based on the Internet of Things (IoT) and Artificial Intelligence(AI), and outlines its applications in ventilation, lighting, and photovoltaic systems. Research shows that establishing a three-tier perceptionpredictioncontrol framework in ventilation systems, supported by real-time sensor monitoring and AI optimization, can significantly enhance energy efficiency. Lighting systems employing millimeter-wave radar and adaptive dimming technologies effectively reduce false detections and energy waste. Photovoltaic systems integrated with building designs and coordinated with energy storage models can improve energy self-sufficiency. The multidimensional technical synergy of IoT platforms, AI optimization, and user participation further validates the systems effectiveness in reducing energy consumption and supporting carbon neutrality, providing a feasible path for energy savings in smart buildings.
Yuanchun Zou (Wed,) studied this question.