A learning approach for energy efficiency optimization by occupancy detection

Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST

Volumn 150, Issue , 2015, Pages 9-15

  Mansur, Vitor ^a   Carreira, Paulo ^a,b   Arsenio, Artur ^c,d  

^a UNIVERSITY OF LISBON   (Portugal)

^b INESC ID   (Portugal)

^c UNIVERSITY OF BEIRA INTERIOR   (Portugal)

^d YDREAMS   (Portugal)

Author keywords

Energy savings; HVAC system; Occupancy detection; Thermal comfort; Users preferences

Indexed keywords

AIR CONDITIONING; AUTOMATION; CLIMATE CONTROL; ENERGY CONSERVATION; ENERGY UTILIZATION; INTELLIGENT BUILDINGS; INTERNET; INTERNET OF THINGS; THERMAL COMFORT;

BUILDING AUTOMATION SYSTEMS; ENERGY EFFICIENCY OPTIMIZATIONS; HVAC SYSTEM; OCCUPANCY DETECTIONS; OCCUPANT PREFERENCES; REDUCING ENERGY CONSUMPTION; USERS PREFERENCES; VENTILATION AND HEATING;

ENERGY EFFICIENCY;

EID: 84948745735     PISSN: 18678211     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-319-19656-5_2     Document Type: Conference Paper

References (9)

1. Yang, R., Wang, L.: Development of multi-agent system for building energy and comfort management based on occupant behaviors. Energy Build. 56, 1–7 (2013)
2. Soucek, S., Zucker, G.: Current developments and challenges in building automation. e & i Elektrotech. und Informationstechnik 129(4), 278–285 (2012)
3. Boman, M., Davidsson, P.: Energy saving and added customer value in intelligent buildings. In: International Conference on the Practical Application of Intelligent Agents and Multi- Agent Technology, vol. 1, pp. 505–516 (1998)
4. Klein, L., Kwak, J., Kavulya, G., Jazizadeh, F., Becerik-Gerber, B., Varakantham, P., Tambe, M.: Coordinating occupant behavior for building energy and comfort management using multi-agent systems. Autom. Constr. 22, 525–536 (2012)
5. Padmanabh, K., Adi Malikarjuna V.: iSense: a wireless sensor network based conference room management system. In: Proceedings of the First ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings, pp. 37–42 (2009)
6. Mansur, V.: Energy Efficiency Optimization Through Occupancy Detection and User Preferences. Instituto Superior Tecnico, MsC Thesis (2014)
7. Arsenio, A.: Development of neural mechanisms for machine learning. Int. J. Neural Syst. 15 (1–2), 41–54 (2011)
8. MacKay, D.: Information Theory, Inference and Learning Algorithms, pp. 316–322. Cambridge University Press, New York (2003)
9. Sun, Z., Wun, Y.: Multispectral image compression based on fractal and K-Means clustering. In: 1st International Conference on Information Science and Engineering, (1), pp. 1341–1344 (2009)