**3. Case study: deploying AI solution to airside energy efficiency improvement**

#### **3.1 Energy consumption in air conditioning systems**

As illustrated in **Figure 3**, by 2050, worldwide power consumption is expected to have doubled from what it is today. Although it is questionable whether the sharp r*ise* in power use is related to the sharp r*ise* in cooling and heating requirements, the fact that there are currently 1.9 billion air conditioning units worldwide serves as proof. Additionally, it is anticipated that by 2050, cooling and heating requirements will have increased by 37%. Therefore, the *road map for* net-zero carbon buildings requires immediate effort to increase the efficiency of the air conditioning systems and the occupants' behav*ior*, incorporate cutting-edge control systems, and embrace passive technologies. This project aims to increase air conditioning system's efficiency by integrating them with AI-focused self-learning control systems.

A case study was carried out at one of the spacious offices at the Singapore Institute of *Technology (SIT*) to apply AI to air conditioning systems. Due to its tropical climate, space cooling is required throughout the year, and the building sector accounts for 37% of total energy consumption. **Figure 5** depicts the energy consumption of the air conditioning system, which is as high as 50% of building energy consumption due to its hot and humid climate. A detailed breakdown of the energy consumption of HVAC systems is shown in **Figure 5**, and airside accounted for 34% of the total energy consumption of HVAC systems. Although the airside energy consumption is *equall*y important compared to the waterside, it is mostly overlooked due to the high dynamics in nature.

**Figure 5.**

*Breakdown of energy consumption of buildings in Singapore [11].*
