Can HVAC really learn from users? A simulation-based study on the effectiveness of voting for comfort and energy use optimization

A prototype solution is described and evaluated by simulation. We show that ambient intelligent systems can be used to control a building's EMS, effectively reducing energy consumption while maintaining acceptable comfort levels. Our results indicate that employing a k-means machine learning technique enables the automatic configuration of an HVAC system to reduce energy consumption while keeping the majority of occupants within acceptable comfort levels. The developed prototype provides occupants with feedback on ambient variables on a mobile user interface. © 2017 Elsevier Science. All rights reserved.