11 May 2021

EkkoSense Cooling Advisor provides data centre operations teams with focused cooling performance recommendations and advisory actions. Built right into the heart of its 3D visualisation and analytics software, Cooling Advisor is the industry’s first embedded advisory solution.

It helps organisations to unlock significant data centre cooling energy savings – just by acting on the software’s advice alone. 

Cooling Advisor’s actionable changes – such as suggested optimum cooling unit set points, changes to floor grille layouts, checking that cooling units are running to specification, fan speed adjustments or advice on optimum rack locations – are based on powerful AI and machine learning analytics.

Recommendations are presented each time for human auditability before team members make the suggested changes.

They can then use EkkoSense’s data centre performance optimisation solution to confirm that Cooling Advisor recommendations are delivering the expected results.

With the latest software from EkkoSense already unlocking data centre cooling energy savings of up to 30% per annum, Cooling Advisor goes one step further.

It provides clear recommended actions that take advantage of EkkoSense’s PhD-level optimisation expertise to equip data centre teams with a powerful self-optimisation capability.

By adopting analytics and machine learning, EkkoSense ensures that Cooling Advisor delivers advice that is specific to each data centre room.

This approach recognises that data centres never stay the same.

Using Cooling Advisor and following its recommendations will allow operations teams to unlock a further 10% saving on their data centre cooling costs.

Additionally, by deploying cooling duty sensors to track cooling loads, EkkoSense is also able to identify undetected cooling unit faults before they are even picked up by BMS alerts.

By capturing entirely new levels of data centre cooling data, including energy usage and airflow distribution, EkkoSense is also able to map zone-by-zone cooling analytics within the data centre to help with resiliency and capacity planning decisions.

The application of analytics and machine learning here will show which AHU units are servicing which racks, allowing Cooling Advisor to identify which AHUs could be put into standby or turned down if using variable speed fans. ekkosense.com