Cooling Intelligence
Transform your data center cooling from reactive maintenance to predictive optimization. Reduce PUE, eliminate hot spots, and maximize free cooling hours with AI-driven thermal intelligence.
Cooling Intelligence Services
Thermal optimization, airflow analysis, chiller efficiency, and predictive hot-spot management for maximum cooling performance.
Thermal Topology Mapping
3D visualization of thermal gradients across the data center floor, identifying hot spots and cold spots for optimal airflow management.
- Visual heat mapping
- Hot spot identification
- Airflow optimization
Predictive Hot-Spot Detection
Machine learning models that predict thermal anomalies before they occur, enabling proactive cooling adjustments.
- Early warning alerts
- Prevent equipment damage
- Reduce emergency cooling
Chiller Efficiency Optimization
Real-time optimization of chiller plant operations to minimize energy consumption while maintaining cooling capacity.
- Lower energy costs
- Extended equipment life
- Optimal performance
Airflow Analysis & Optimization
CFD-validated analysis of airflow patterns to eliminate bypass air, reduce recirculation, and improve cooling efficiency.
- Eliminate bypass air
- Reduce recirculation
- Improve PUE
Free Cooling Maximization
Intelligent control strategies to maximize economizer hours and reduce mechanical cooling dependency.
- Maximize free cooling
- Reduce compressor runtime
- Lower carbon footprint
Case Studies
Real-world results from organizations that transformed their cooling operations.
Enterprise Colocation Provider
Challenge
Persistent hot spots causing customer SLA violations and emergency cooling costs of $180K annually
Solution
Deployed predictive hot-spot detection with automated CRAC adjustments
Results
- Zero thermal SLA violations in 18 months
- Emergency cooling costs eliminated
- PUE improved from 1.62 to 1.41
Regional Healthcare System
Challenge
Aging chiller plant consuming 40% of total facility energy with frequent maintenance issues
Solution
Implemented chiller optimization with predictive maintenance integration
Results
- 28% reduction in cooling energy
- Maintenance costs reduced by 45%
- Chiller life extended by 5+ years
Technical Specifications
Precision thermal intelligence built for enterprise data centers with seamless integration into existing BMS and DCIM platforms.
Cooling System Integration
- CRAC/CRAH units (Liebert, Schneider, Vertiv)
- Chiller plants and cooling towers
- In-row and rear-door cooling
- BMS platforms (Honeywell, Johnson Controls)
- Environmental monitoring systems
Frequently Asked Questions
How does predictive hot-spot detection work?
Our system uses machine learning models trained on historical thermal data, workload patterns, and environmental conditions. By analyzing trends in temperature, airflow, and IT load, the system can predict thermal anomalies 2-4 hours before they occur, allowing proactive cooling adjustments.
What sensors are required for thermal mapping?
We integrate with existing temperature sensors in your CRAC/CRAH units, in-row cooling, and any deployed environmental monitoring systems. For enhanced granularity, we recommend rack-level temperature sensors at inlet and exhaust positions. Our platform supports BACnet, Modbus, and SNMP protocols.
Can you optimize existing chiller plants?
Yes. Our chiller optimization works with existing equipment by adjusting setpoints, sequencing, and staging based on real-time conditions and predicted demand. We integrate with most major BMS platforms and can deliver 15-30% energy savings without capital equipment replacement.
How much can free cooling save?
Savings depend on climate and current economizer utilization. Typically, we increase economizer hours by 20-40%, translating to 10-25% reduction in total cooling energy. In favorable climates, some facilities achieve over 5,000 free cooling hours annually.