Personalized sensing towards building energy efficiency and thermal comfort

Abstract

The emergence of Information Technology (IT) based sensing has received increasing attention and acceptance in buildings due to its noninvasive nature and its ability in delivering real-time and potentially highly personalized feedback to building energy and comfort management. This study presents results of a pilot deployment experiment on such an IT-based sensing system - Personal Office Energy Monitor (POEM) developed by Intel Labs. The pilot study shows that with appropriate analytic methods the POEM sensor data could be transferred into valuable inputs to building management system (BMS). This study applies building science principle based models as the first step to calculate intermediate building performance indices based on raw measurement data. The intermediate performance indices are then further analyzed in order to reveal potential means to improve a building's operational energy efficiency and occupant comfort. Results demonstrate that POEM sensor data could lead to energy saving opportunities through localized comfort management, plug load sensing and scheduling, and occupancy based building control. As an IT platform-integrated and occupant centered sensing system, POEM provides a convenient, low-cost, and efficient sensing solution to the next generation of smart buildings, featured by its ability in assisting BMS to improve operational building energy efficiency without compromising occupants' thermal comfort and indoor environmental quality.