AI-Enhanced Resilience for Data Centers in Arid Cities: Sustainable Cooling, Predictive Control, and Climate-Aware Cost Optimization

Qatar’s rapid expansion of cloud computing, generative AI, and digital services has made data centers vital infrastructure, yet their operation in arid climates faces challenges of extreme heat, dust, water scarcity, and high cooling energy demand—accounting for 36% of national electricity use. This project proposes an AI-driven framework for resilient, sustainable data centers optimized for desert conditions. Using machine learning, edge AI, and digital twins, the system will enable real-time thermal optimization, predictive HVAC maintenance, smart resource use, and adaptive control during climate stress events. A hybrid testbed will simulate extreme scenarios, while thermal engineering expertise will guide the validation of advanced cooling solutions. Integration of renewables and storage (batteries, hydrogen, liquid CO₂) will enhance flexibility, and novel climate-aware cost metrics—such as cost-per-joule of cooling—will inform investment planning. Expected outcomes include a validated AI-powered digital twin, reductions in cooling energy, water, and emissions, predictive control tools for emergency response, policy recommendations for scalable deployment, and strengthened industry partnerships. The project advances Qatar’s leadership in sustainable digital infrastructure and contributes to global data center resilience in arid regions.

Hamad Bin Khalifa University (HBKU)