2019 CSCE Annual Conference - Laval (Greater Montreal) Conference
Dr. Susan M. Bogus, University of New Mexico
Dr. Andrea Mammoli, University of New Mexico
More than half of commercial building stock in the United States were built before 1980 with a median age of 32 years in 2012. In the age of Smart and Green buildings, owners tend to incorporate expensive sensor infrastructure to reduce building energy consumption and improve the building occupants’ satisfaction, efficiency, and comfort levels. In this context, studies explored the influence of building occupancy on its energy consumption. Recently, researchers shifted their focus towards exploring different occupancy estimation techniques with both dedicated sensors and existing infrastructure (e.g. CO2 sensors, Smart meters, temperature and humidity sensors, and wi-fi networks). However, there are concerns about the cost effectiveness, computational effort, accuracy and privacy protection for existing techniques. This study explores the usage of number of IP addresses connected to a wi-fi router to estimate the occupancy within a building. To this end, occupancy patterns in a thirty-year-old university building are estimated using existing wi-fi infrastructure and compared and calibrated to ground data obtained manually and from dedicated occupancy estimating sensors to evaluate the accuracy. The estimated occupancy data patterns using existing wi-fi network represent a cost-effective method of occupancy estimation with less computational processing and reduced privacy concerns, that could assist owners in the decision-making process towards investing into smart and energy efficient technologies.