SingaporeLogistics and transport2023 – ongoingSMRT Corporation
Green Station predictive AI for air-conditioning control
SMRT reported 6% to 8% lower cooling energy use in Green Station trials
Problem
SMRT identified overcooling at Paya Lebar and MacPherson stations as a source of energy waste.
Approach
Green Station combined facilities management with AI-enabled energy controls. Predictive, demand-based controls adjusted air-conditioning settings while maintaining commuter comfort. SMRT tested the system at the 2 Circle Line stations.
Results
Takeaway
The disclosed savings came from initial station trials. Savings from a network-wide rollout remained projections.
Categories
- Size
- Large enterprise
- Industry
- Logistics and transport
- Business function
- Production and quality
- Innovation type
- Process innovation
- AI technology
- Predictive analytics and MLOptimization
- Adoption
- Built in-house
- Goal
- Cost savings
- Evidence
- Company's own claim
Sources
Source summaries
SMRT described predictive AI controls and initial trials at Paya Lebar and MacPherson stations. It reported a 6% to 8% reduction in cooling energy consumption and separately presented projected savings from wider deployment.
Full details are in the original sources.
