Buildings' Energy and Comfort Efficiency
Motivation
Heating, ventilating, and air conditioning (HVAC) systems
account for 51% of the total energy usage in buildings. Adaptive
lighting, variable air volume hoods, indirect evaporative
pre-cooling, and demand response systems are important for
achieving energy efficient sustainable buildings. However, the
current state of these technologies will only take us so far
towards achieving the net-zero energy buildings. The majority of
these systems assume maximum room occupancy; all rooms are
conditioned without regard to actual usage. For example, a
conference room could be conditioned assuming an occupancy of 30
people when only 20 people actually use the room. Also, it is
possible to avoid conditioning the room when empty. Thus,
effective energy management requires real-time occupancy
measurement. A system for occupancy monitoring is essential to
solving this fundamental energy management problem. Perhaps just
as important as an occupancy estimation system is occupancy
prediction models. This needs to be addressed since conditioning
a room is not instantaneous and requires time for adjustments.
For example, if it is known that a large number of people are in
a lobby area, we want the HVAC system to know an adjacent
conference room will be used with high probability and begin
conditioning the room beforehand.
SCOPES - Smart Camera Object Position Estimation System
SCOPES, a distributed Smart Cameras Object Position Estimation
System that balances the trade-offs associated with camera sensor
networks. Each node in the system is comprised of a Cyclops
camera that performs local detection and processing of the visual
information and a Tmote sensor node, which provides power and
multi-hop communication capability. SCOPES uses local adaptive
techniques to maximize the the active sensing time of the camera.
The system switches between fast and simple background
subtraction algorithms for object detection and the more
computationally intensive pixel grouping algorithms for
estimating the number and direction of travel of multiple persons
in the local field of view. By aggregating meta-information
generated by each node, SCOPES is able to minimize the total data
transmitted in the network and still be able to generate an
accurate density estimation map of the coverage area.
SCOPES Software Block Diagram
Click
here for
additional images.
Boundary Locations

This figure shows the boundary locations that transitions are
currently being monitored. These locations are placed
strategically such that the occupancy of several rooms can be
monitored.
Occupancy Modeling
Models of occupancy can be created by gathering data over a
long period of time using a system such as SCOPES. We have
developed a Multivariate Gaussian model and an agent based model
using several days of ground truth occupancy data. The agent
based model simulates occupancy by modeling the behavior of the
individual. Agents are given paths, walking speed, and iterates
based on the occupancy changes seen in the training data.
Occupancy is simulated by creating multiple agents that follow
probabilistically generated instructions. Based on their
simulated movement, room occupancies over the course of the day
can be estimated. The multivariate Gaussian model creates a
Gaussian fit of room occupancies for each hour. These fits allows
us to calculate probabilities for occupancy changes over time.
Currently we are developing models based on Gaussian mixture
models and Markov chains. These models are useful design tools
for simulating how occupants utilize space. In particular, these
models can be used for creating control strategies for HVAC
systems.
Energy Savings
Using occupancy models to examine user mobility patterns in
buildings, we can predict room usage thereby enabling us to
control the HVAC systems in an adaptive manner. By controlling
HVAC using a multivariate Gaussian model and an agent based model
occupancy predictions, simulations indicate a 14% reduction in
HVAC energy usage by having an optimal control strategy based on
occupancy estimates and usage patterns.
Publications
- Erickson13a
-
Varick Erickson, Stefan Achleitner,
Alberto E. Cerpa, "POEM:
Power-efficient Occupancy-based Energy Management
System," Proceedings of the
Twelfth ACM/IEEE International Conference on Information
Processing on Sensor Networks (IPSN 2013),
pp. 14 pages, ACM/IEEE, Philadelphia, PA, USA, April, 2013.
- Erickson12a
-
Varick Erickson, Alberto E.
Cerpa, "Thermovote: Participatory
Sensing for Efficient Building HVAC Conditioning,"
Proceedings of the Fourth ACM
Workshop on Embedded Sensing Systems for Energy-Efficiency in
Buildings (BuildSys 2012), pp.
9--16, ACM, Toronto, Ontario, Canada, 2012.
- Zaveri11a
-
Siddharth Zaveri, Shane Ross, Varick
Erickson, Ankur U. Kamthe, Tao Liu, Alberto E. Cerpa,
"Building Energy Management Systems
Actuated Using Wireless Camera Sensor Network,"
Proceedings of the Third ACM Workshop
on Embedded Sensing Systems for Energy-Efficiency in
Buildings (BuildSys 2011), pp.
39--40, Seattle, WA,
USA, 2011.
- Kamthe11b
-
Ankur Kamthe, Miguel A.
Carreira-Perpinan, Alberto E. Cerpa, "Enabling Building Energy Auditing Using Adapted
Occupancy Models," Proceedings
of the Third ACM Workshop on Embedded Sensing Systems for
Energy-Efficiency in Buildings (BuildSys 2011),
pp. 33--38, Seattle, WA, USA, 2011.
- Erickson11a
-
Varick Erickson, Miguel A.
Carreira-Perpinan, Alberto E. Cerpa, "OBSERVE: Occupancy-based system for efficient
reduction of HVAC energy," Proceedings of the Tenth ACM/IEEE International
Conference on Information Processing on Sensor Networks (IPSN
2011), pp. 258--269,
ACM/IEEE, Chicago, IL, USA, April, 2011.
- Erickson10a
-
Varick Erickson, Alberto E.
Cerpa, "Occupancy based demand
response HVAC control strategy," Proceedings of the Second ACM Workshop on
Embedded Sensing Systems for Energy-Efficiency in Buildings
(BuildSys 2010), pp. 7--12,
ACM, Zürich, Zürich
Canton, Switzerland, November, 2010.
- Sohn10a
-
Michael D. Sohn, Doug R. Black, Phillip
N. Price, Yiqing Lin, Rohini Brahme, Amit Surana, Satish
Narayanan, Alberto Cerpa, Varick Erickson, Ankur
Kamthe, "Occupancy-Based Energy
Management in Buildings: Final Report to Sponsors,"
LBNL Technical Report,
pp. 1--58, Ernest Orlando Lawrence Berkeley National Laboratory
(LBNL), Berkeley, CA,
USA, June, 2010.
- Erickson09a
-
Varick L. Erickson, Yiqing Lin, Ankur
Kamthe, Rohini Brahme, Alberto E. Cerpa, Michael D. Sohn,
Satish Narayanan, "Energy
Efficient Building Environment Control Strategies Using
Real-time Occupancy Measurements," Proceedings of the 1st ACM Workshop On Embedded
Sensing Systems For Energy-Efficiency In Buildings (BuildSys
2009), pp. 19--24,
ACM, Berkeley, CA, USA, November, 2009.
- Kamthe09a
-
Ankur Kamthe, Lun Jiang, Matt Dudys,
Alberto Cerpa, "SCOPES: Smart
Cameras Object Position Estimation System,"
Proceedings of the Sixth European
Conference on Wireless Sensor Networks (EWSN 2009),
pp. 279--295, Springer-Verlag, Cork,
Munster, Ireland, February,
2009.
- Kamthe08a
-
Ankur Kamthe, Lun Jiang, Alberto Cerpa,
Matt Dudys, Edward Smith, "SCOPES:
Smart Cameras Object Position Estimation System,"
UC Merced Research Poster
Competition, Merced, CA,
USA, March, 2008.
- Kamthe07a
-
Ankur Kamthe, Lun Jiang, Alberto
Cerpa, "SCOPES: Smart Cameras
Object Position Estimation System," UCM Technical Report TR-2007-002, pp. 1--17, University of
California, Merced, June,
2007.
- Cerpa06a
-
Alberto Cerpa,, "Sensor Network Challenges for Intelligent
Buildings," Proceedings of the
National Workshop on Beyond SCADA: Networked Embedded Control
for Cyber Physical Systems, pp. 2
pages, Networking and Information
Technology Research and Development (NITRD),
Pittsburgh, PA, USA,
November, 2006.
People
Sponsors
