Alex Beltran, Varick L. Erickson, Alberto E. Cerpa
In order to achieve sustainability, steps must be taken to reduce energy consumption. In particular, heating, cooling, and ventilation systems, which account for 42% of the energy consumed by US buildings in 2010 [8], must be made more efficient. In this paper, we demonstrate ThermoSense, a new system for estimating occupancy. Using this system we are able to condition rooms based on usage. Rather than fully conditioning empty or partially filled spaces, we can control ventilation based on near real-time estimates of occupancy and temperature using conditioning schedules learned from occupant usage patterns. ThermoSense uses a novel multisensor node that utilizes a low-cost, low-power thermal sensor array along with a passive infrared sensor. By using a novel processing pipeline and sensor fusion, we show that our system is able measure occupancy with a RMSE of only ≈0.35 persons. By conditioning spaces based on occupancy, we show that we can save 25% energy annually while maintaining room temperature effectiveness.
Alex Beltran, Varick L. Erickson, Alberto E. Cerpa, "ThermoSense: Occupancy Thermal Based Sensing for HVAC Control," Proceedings of the Fifth ACM Workshop on Embedded Sensing Systems for Energy-Efficient Buildings (BuildSys 2013), pp. 11:1--11:8, ACM, Rome, Province of Rome, Italy, 2013.
@Conference{Beltran13a,
author = "Alex Beltran and Varick L. Erickson and Alberto E.
Cerpa",
title = "ThermoSense: Occupancy Thermal Based Sensing for
{HVAC} Control",
booktitle = "Proceedings of the Fifth ACM Workshop on Embedded
Sensing Systems for Energy-Efficient Buildings
(BuildSys 2013)",
year = "2013",
pages = "11:1--11:8",
address = "Rome, Province of Rome, Italy",
publisher = "ACM",
ISBN = "978-1-4503-2431-1",
articleno = "11",
doi = "10.1145/2528282.2528301",
acmid = "2528301",
keywords = "HVAC Control, Occupancy Sensing, Thermal Sensing",
URL = "http://www.andes.ucmerced.edu/papers/Beltran13a.pdf",
accept = "40",
}