Global AI Challenge for Building E&M Facilities presents Gold Award to Lingnan’s AI Model predicting cooling demand in commercial buildings

Hong Kong’s commercial buildings are often perceived as being excessively cold, which contributes to an unnecessary waste of energy and carbon emissions. A doctoral research team from Lingnan University’s School of Data Science (SDS) has developed an artificial intelligence (AI) model to predict cooling loads precisely, thereby significantly improving energy efficiency. The project recently won the Gold Award at the Global AI Challenge for Building E&M Facilities 2025, and the technology has already been tested successfully in a commercial building in Hong Kong and in the Das Intellitech Building in Shenzhen, both trials showing a strong predictive performance.

The award-winning project “Dynamically engineered multi-modal feature learning for predictions of office building cooling loads” was supervised by Prof S. Joe Qin, President and Wai Kee Kau Chair Professor of Data Science at Lingnan University, and Prof Mo Yanfang, Assistant Professor of the Division of Industrial Data Science of SDS, and team members included Dr Liu Yiren, Postdoctoral Fellow of the Division of Industrial Data Science of SDS, and PhD students Mr Li Jicheng and Mr Zhu Zhongxi from SDS. For the competition, the system accurately predicted the hourly cooling load requirements of four buildings in the month ahead. It also provided optimised control strategies for the HVAC (Heating, Ventilation, and Air Conditioning) systems, maintaining comfortable indoor temperatures, and reduced energy consumption and carbon emissions. The project received the Gold Award of the “Build Your AI Model” academic group, and a prize of US$5,000.