Johnson Controls Brings Cooling Expertise to Singapore’s 200 MW AI Data Center Push

On Jurong Island, a live testing ground for next-generation AI infrastructure is taking shape, and Johnson Controls has now joined the effort. The company announced on Sept. 28, 2026 that it is participating in the Sustainable Tropical Data Centre Testbed (STDCT) 2.0, a programme hosted at the College of Design and Engineering (CDE) at the National University of Singapore (NUS).

Described as a global leader in thermal management, mission-critical building systems, energy efficiency, and decarbonization, Johnson Controls contributes thermal management technologies, smart controls, engineering expertise, and operational experience to the collaboration.

Why the Tropics Test Data Centres Harder

High temperatures and humidity in tropical environments present unique challenges for cooling performance, making efficient and reliable infrastructure all the more important. Professor Lee Poh Seng, programme director of STDCT and head of the Department of Mechanical Engineering at NUS CDE, explained that AI is fundamentally changing the design envelope for data centres, with much higher rack densities placing unprecedented demands on cooling, power, controls, and resource efficiency.

"STDCT 2.0 is designed to move beyond individual technologies and evaluate how these systems can be integrated and optimised as one infrastructure platform under real tropical operating conditions," said Professor Lee. "Johnson Controls brings deep expertise in thermal management, controls, and mission-critical infrastructure to this collaboration."

STDCT 2.0 brings together industry and academia to evaluate emerging AI and data centre technologies under real-world tropical conditions. It forms part of a broader initiative with JTC Corporation and industry partners to transform Jurong Island into a living testbed for next-generation, low-carbon and AI-ready infrastructure.

Squeezing More Computing From the Same Power

Johnson Controls frames its role around the most critical constraints to responsible AI growth: power availability, water consumption, and infrastructure capacity. Using an integrated portfolio of thermal management technologies, the company aims to optimise the entire thermal ecosystem to improve efficiency and create additional computing capacity from existing power and infrastructure resources.

The company cited a modelled design in which this integrated approach can reduce non-IT energy consumption by up to 50% compared with conventional cooling methods. Waste heat recovery is another focus.

Johnson Controls is pursuing additional AI computing capacity from energy that would otherwise be lost as waste heat. In a 1-gigawatt data centre blueprint, the company's absorption chiller reference design demonstrated the potential to convert the 57% of energy typically lost as waste heat from on-site power generation into productive cooling.

According to the company, this would enable up to 97 MW of additional AI computing capacity from existing power infrastructure while reducing cooling-related electrical demand by up to 44%.

Austin Domenici, president of Data Centre Solutions at Johnson Controls, placed the collaboration within a broader rethinking of infrastructure design.

"Meeting the demands of advanced computing requires a new way of thinking about infrastructure," Domenici said. "As AI workloads continue to grow, success will depend not only on computing power but also on how efficiently we manage the resources behind it. Johnson Controls brings expertise across the full thermal ecosystem, helping customers improve efficiency, reduce resource consumption, and enable greater computing capacity. This collaboration is an opportunity to explore and validate new approaches to infrastructure that can support the future of AI."

Scaling AI in a Power-, Water-, and Space-Constrained Nation

The announcement comes as Singapore recently allocated an additional 200 MW of data centre capacity as the country expands its low-carbon digital infrastructure.

According to the release, the programme explores pathways to scale AI efficiently in power-, water- and space-constrained environments, and research from the collaboration will help inform more efficient infrastructure designs for Singapore and other tropical markets. The testbed's launch coincides with Singapore's efforts to expand data centre capacity in a resource-constrained environment.

With the additional 200 MW allocated and the island nation's power, water and space limits, the programme is positioned as a way to evaluate how AI infrastructure can scale efficiently under tropical operating conditions. Johnson Controls' participation adds industry expertise in thermal management and controls to the academic-led testbed, with findings intended to inform future data centre design across Singapore and other tropical markets where heat and humidity complicate cooling performance.

Research, Talent, and a Regional Ambition

Beyond evaluating next-generation technologies, STDCT 2.0 will support research, talent development and industry collaboration. Johnson Controls and NUS CDE will work to accelerate opportunities for advanced research, workforce training, innovation and knowledge sharing to support the continued growth of the data centre sector.

Ali Badreddine, vice president and general manager for Southeast Asia Business and Asia Pacific Data Centre Solutions at Johnson Controls, noted that the collaboration arrives as AI drives a new wave of infrastructure demand across Asia Pacific.

"Advancing research, developing talent and strengthening industry collaboration will be critical to meeting that growth responsibly," Badreddine said. "STDCT 2.0 brings these elements together to help advance AI-ready infrastructure across Singapore and the broader Asia Pacific region."

The signing ceremony for the collaboration was attended by Dr. Ursula Oesterle, vice president (Industry) at the National University of Singapore; Professor Lee Poh Seng; Badreddine; and Domenici.