Enabling building energy auditing using adapted occupancy models

BuildSys 2011 - Proceedings of the 3rd ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings, Held in Conjunction with ACM SenSys 2011

Volumn , Issue , 2011, Pages 31-36

  Kamthe, Ankur ^a   Erickson, Varick ^a   Carreira Perpĩán, Miguel Á ^a   Cerpa, Alberto ^a  

^a Embedded Systems and Automation Laboratory   (United States)

Author keywords

energy saving; HVAC; machine learning; model adaptation; occupancy

Indexed keywords

BUILDING ENERGY CONSUMPTION; ENERGY REGULATION; HVAC; INCREASING ENERGY COSTS; LONG-TERM IMPACTS; MODEL ADAPTATION; OCCUPANCY; TARGET TEMPERATURE;

BUILDINGS; ENERGY CONSERVATION; ENERGY EFFICIENCY; ENERGY POLICY; ESTIMATION; LEARNING SYSTEMS; SENSORS;

ENERGY UTILIZATION;

EID: 84875207429     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2434020.2434028     Document Type: Conference Paper

References (17)

1. 2010 Building Energy Data Book. U.S. Dept. of Energy, 2011.
2. Y. Agarwal, B. Balaji, S. Dutta, R. K. Gupta, and T. Weng. Dutycycling buildings aggressively: The next frontier in HVAC control. In IPSN'11.
3. C. M. Bishop. Pattern Recognition and Machine Learning. Springer-Verlag, 2006.
4. M. J. Brandemuehl and J. E. Braun. The impact of demand-controlled and economizer ventilation strategies on energy use in buildings. ASHRAE Transactions, 1999.
5. D. T. Delaney, G. M. P. O'Hare, and A. G. Ruzzelli. Evaluation of energy-efficiency in lighting systems using sensor networks. In BuildSys '09.
6. R. Dodier, G. Henze, D. Tiller, and X. Guo. Building occupancy detection through sensor belief networks. Energy & Buildings, 2006.
7. V. Erickson, Y. Lin, A. Kamthe, R. Brahme, A. Cerpa, M. Sohn, and S. Narayanan. Energy efficient building environment control strategies using real-time occupancy measurements. In BuildSys, 2009.
8. V. L. Erickson,M. Á. Carreira-Perpiñán, and A. E. Cerpa. OBSERVE: Occupancy-based system for efficient reduction of HVAC energy. In IPSN'11.
9. J.-L. Gauvain and C.-H. Lee. Bayesian learning for hidden Markov model with Gaussian mixture state observation densities. Speech Communication, 11(2-3):205-213, June 1992.
10. A. Kamthe, M. Á. Carreira-Perpiñán, and A. Cerpa. Adaptation of a mixture of multivariate bernoulli distributions. In IJCAI 2011.
11. A. Kamthe, L. Jiang, M. Dudys, and A. Cerpa. SCOPES: Smart cameras object position estimation system. In EWSN, 2009.
12. M. Krarti. Energy audit of building systems: An engineering approach. CRC Press, 2011.
13. C. J. Leggetter and P. C. Woodland. Maximum likelihood linear regression for speaker adaptation of continuous density hidden Markov models. Computer Speech and Language, 9(2):171-185, Apr. 1995.
14. G. J. McLachlan and T. Krishnan. The EM Algorithm and Extensions. John Wiley & Sons, second edition, 2008.
15. G. R. Newsham and B. J. Birt. Building-level occupancy data to improve ARIMA-based electricity use forecasts. In BuildSys '10.
16. A. Rice, S. Hay, and D. Ryder-Cook. A limited-data model of building energy consumption. In BuildSys '10.
17. T. Teixeira and A. Savvides. Lightweight people counting and localizing in indoor spaces using camera sensor nodes. ICDSC, 2007.