As data consumption—and with it, AI, cloud computing, and high-density workloads—surges in Singapore, conventional DCIM (Data Centre Infrastructure Management) systems are struggling to keep pace. In 2025, simply monitoring infrastructure with static dashboards and annual reports isn’t enough. The future belongs to data-driven cooling powered by AI and real-time optimisation.
Legacy DCIM tools often rely on static reporting, reactive incident management, and lack the granular thermal control needed for today’s complex environments. In Singapore’s humid climate, where cooling accounts for up to 40% of a data centre’s energy consumption, this gap translates directly into higher costs, sustainability challenges, and operational risks.
Why Traditional DCIM Falls Short
Traditional DCIM systems were designed to provide visibility into IT and facility assets. While useful, they are often complex, expensive, and reactive in nature. Legacy DCIMs tend to:
- Focus on static reporting instead of continuous optimisation.
- Provide limited thermal insights, often missing the “invisible” hotspots at the rack level.
- Lack integration with modern hybrid cooling architectures (air and liquid cooling).
- Fail to deliver actionable intelligence for sustainability and ESG compliance.
This is particularly problematic in Singapore, where data centres already consume around 7% of the nation’s total electricity—a share projected to rise to 12% by 2030 if left unchecked. Without smarter, data-driven cooling, the sector risks unsustainable growth in both costs and carbon footprint.
The Rise of AI-Powered Data-Driven Cooling
The next generation of cooling management is about making the invisible visible. Platforms like EkkoSense, powered by AI and machine learning, go beyond DCIM by offering:
- Real-time thermal monitoring with granular visibility across racks and rooms.
- Digital twin visualisation that lets operators model “what-if” scenarios.
- Automated Cooling Advisor insights that identify optimisation opportunities.
- Cooling anomaly detection to catch risks before failures occur.
- Embedded ESG reporting for regulatory compliance with CSRD, EED, and ISO standards.
These innovations are already being validated locally. For example, Red Dot Analytics’ AI-powered digital twins have demonstrated 5–30% cooling energy and carbon reductions in Singapore data centres. Similarly, reinforcement-learning-based control models tested on NSCC servers achieved 11–15% savings on real cooling workloads.
Why 2025 Is the Turning Point
Several forces are converging to make 2025 a critical year for Singapore’s data centres:
- Climate Realities
Singapore’s tropical climate makes cooling far more energy-intensive than in temperate countries. Here, cooling can account for 30–50% of a data centre’s total energy use, compared to just 15–30% in cooler climates. With data centres already consuming 7% of the nation’s electricity—set to reach 12% by 2030 if unaddressed, optimisation is both an economic and environmental imperative. - Regulatory Momentum
The Singapore government is setting clear benchmarks to curb rising energy demand. The SS697:2023 standard encourages operators to raise facility operating temperatures to 26 °C or higher, saving 2–5% cooling energy for every 1 °C increase. Building on this, the new SS715:2025 IT equipment standard requires hardware to be 30% more energy-efficient and operable at up to 35 °C, creating further opportunities to cut cooling overheads. . - Emerging Innovations
Singapore’s research ecosystem is driving the next wave of sustainable cooling. At the NUS/NTU-led STDCT testbed, experimental solutions that combine air and liquid cooling have achieved up to 40% reductions in cooling energy, water consumption, and CO₂ emissions. The initiative is also pushing for a PUE of below 1.2, compared to the current local average of 1.3. - Next-Gen Tech Deployment
Private operators are also innovating. Immersion cooling, as deployed by Sustainable Metal Cloud (SMC) in Singapore, has shown potential to cut up to 50% of energy use versus conventional air cooling. Meanwhile, ST Telemedia Global Data Centres (STT GDC) is piloting AI-driven autonomous cooling systems with Phaidra, which dynamically adjust cooling strategies in real-time using live sensor data. - Industry Expansion
Singapore is already home to more than 70 operational data centres, and growth shows no signs of slowing. Operators such as Keppel are planning to expand total capacity from 650 MW today to 1.2 GW in the near term to meet surging AI-driven demand. This rapid scaling amplifies the urgency of adopting more sustainable and intelligent cooling strategies.
The message is clear: data-driven cooling is no longer optional—it’s a competitive necessity.
Partnering with Data Clean Asia for Smarter, Cleaner, Optimised Data Centres
At Data Clean Asia, we understand that optimisation doesn’t stop at software. A truly efficient data centre also depends on a clean, contaminant-free environment to ensure peak performance and reliability. That’s why, as an official partner of EkkoSense, we combine our specialised cleaning services for critical facilities with cutting-edge AI-driven cooling optimisation.
Whether you operate a hyperscale facility, a colocation data hall, or an enterprise server room, our team helps you achieve safer, greener, and more efficient operations.
Contact us today to discover how Data Clean Asia can transform your data centre into a cleaner, smarter, and more sustainable facility.
