| Proj No. | A3017-251 |
| Title | AI-Powered Predictive Modeling for Smart HVAC Optimization |
| Summary | This project explores the use of AI and machine learning to develop a data-driven predictive model for Heating, Ventilation, and Air Conditioning (HVAC) systems, serving as a critical foundation for intelligent control and optimization. The objective is to leverage time-series forecasting techniques, such as Long Short-Term Memory (LSTM), Graph Convolutional Networks (GCN), and Transformer models, to predict temperature and energy consumption. Students will gain hands-on experience in feature engineering, data augmentation, and model optimization. Students must have basic programming skills and be familiar with Python, C++, or MATLAB. This project is ideal for those interested in AI applications in smart buildings, IoT-driven control, and sustainable technology |
| Supervisor | A/P Chau Yuen (Loc:S1 > S1 B1A > S1 B1A 12, Ext: +65 67905420) |
| Co-Supervisor | - |
| RI Co-Supervisor | - |
| Lab | Centre for Information Sciences & System (CISS) (Loc: S2-B4b-05) |
| Single/Group: | Single |
| Area: | Intelligent Systems and Control Engineering |
| ISP/RI/SMP/SCP?: |