Reducing Energy Consumption through Cyber-Physical Adaptive Spaces and Occupants' Biosignals

Abstract

The field of architecture has long embraced adaptive approaches to address issues of sustainability and efficiency. Building energy consumption accounts for about 40% of the total energy consumption in the U.S. This energy is mainly used for lighting, heating, cooling, and ventilation. Researches show that 30% of that energy is wasted. One of the main reasons for such high energy waste in the commercial (and even private) sectors is a generic assumption about the occupants' preferences. To fill this gap, the objective of this project is to optimize building energy retrofits by creating smart environments that autonomously respond to the occupants' comfort level using affective computing and adaptive systems. This adaptive approach will help optimizing energy consumption without sacrificing occupants' comfort through passive cooling and heating strategy, responding to occupants' preferences detected from their biological and neurological data. Progress towards achieving this goal will make building energy costs more affordable to the benefit of families and businesses and reduce energy waste.