• Pedro F. PereiraEmail author
  • Nuno M. M. Ramos
  • João M. P. Q. Delgado
Part of the SpringerBriefs in Applied Sciences and Technology book series (BRIEFSAPPLSCIENCES)


This literature review evidenced a sustained growth, over the last few years, concerning intelligent building studies and occupant behaviour in buildings.


Occupational Behavior Intelligent Building Numerical Simulation Program Comprehension Monitoring Strategies Building Automation Systems (BASs) 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Ahmed HS, Faouzi BM, Caelen J (2013) Detection and classification of the behaviour of people in an intelligent building by camera. Int J Smart Sens Intell Syst 6(4):1317–1342Google Scholar
  2. Bao K, Allerding F, Schmeck H (2011) User behaviour prediction for energy management in smart homes. Comunicação apresentada em Proceedings—2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011Google Scholar
  3. Bekö G, Lund T, Nors F, Toftum J, Clausen G (2010) Ventilation rates in the bedrooms of 500 Danish children. Build Environ 45(10):2289–2295. Scholar
  4. Calì D, Andersen RK, Müller D, Olesen BW (2016) Analysis of occupants’ behaviour related to the use of windows in German households. Build Environ 103:54–69. Scholar
  5. Candanedo LM, Feldheim V, Deramaix D (2017) A methodology based on Hidden Markov Models for occupancy detection and a case study in a low energy residential building. Energy Build 148:327–341. Scholar
  6. Delzendeh E, Wu S, Lee A, Zhou Y (2017) The impact of occupants’ behaviours on building energy analysis: a research review. Renew Sustain Energy Rev 80:1061–1071. Scholar
  7. D’Oca S, Chen CF, Hong T, Belafi Z (2017) Synthesizing building physics with social psychology: an interdisciplinary framework for context and occupant behaviour in office buildings. Energy Res Soc Sci 34:240–251. Scholar
  8. Eurostat (2000) Harmonized European Time User Survey—HETUS. editado por Eurostat.
  9. Fabi V, Andersen RV, Corgnati S, Olesen BW (2012) Occupants’ window opening behaviour: a literature review of factors influencing occupant behaviour and models. Build Environ 58:188–198. <Go to ISI>://WOS:000309332800018CrossRefGoogle Scholar
  10. Guerra-Santin O, Romero Herrera N, Cuerdae E, Keyson D (2016) Mixed methods approach to determine occupants’ behaviour—Analysis of two case studies. Energy Build 130:546–566. Scholar
  11. Hong T, D’Oca S, Turner WJN, Taylor-Lange SC (2015) An ontology to represent energy-related occupant behaviour in buildings. Part I: Introduction to the DNAs framework. Build Environ 92:764–777. Scholar
  12. INE, Instituto Nacional de Estatistica, Direção Geral de Energia e Geologia DGEG (2011) Inquérito ao Consumo de Energia no Sector Doméstico 2010Google Scholar
  13. Jia M, Srinivasan RS, Raheem AA (2017) From occupancy to occupant behaviour: an analytical survey of data acquisition technologies, modeling methodologies and simulation coupling mechanisms for building energy efficiency. Renew Sustain Energy Rev 68:525–540. Scholar
  14. Kvisgaard B, Collet PF (1986) Occupants’ influence on air change in dwellings. Comunicação apresentada em 7th AIC Conference, em Stratford-upon-Avon, UKGoogle Scholar
  15. Mills B, Schleich J (2012) Residential energy-efficient technology adoption, energy conservation, knowledge, and attitudes: an analysis of European countries. Energy Policy 49:616–628. Scholar
  16. Pereira PF, Ramos NMM (2018) Detection of occupant actions in buildings through change point analysis of in-situ measurements. Energy Build 173:365–377. Scholar
  17. Ramos NMM, Curado A, Almeida RMSF (2015) Analysis of user behaviour profiles and impact on the indoor environment in social housing of mild climate countries. Comunicação apresentada em 6th International Building Physics Conference, IBPC 2015, em TurimGoogle Scholar
  18. Stazi F, Naspi F, D’Orazio M (2017) A literature review on driving factors and contextual events influencing occupants’ behaviours in buildings. Build Environ 118:40–66. Scholar
  19. Wei S, Jones R, de Wilde P (2014) Driving factors for occupant-controlled space heating in residential buildings. Energy Build 70:36–44. Scholar
  20. Wilke U, Haldi F, Scartezzini JL, Robinson D (2013) A bottom-up stochastic model to predict building occupants’ time-dependent activities. Build Environ 60:254–264. Scholar
  21. Yao M, Zhao B (2017) Window opening behaviour of occupants in residential buildings in Beijing. Build Environ 124:441–449. Scholar
  22. Zhang S, McClean SI, Scotney BW (2012) Probabilistic learning from incomplete data for recognition of activities of daily living in smart homes. IEEE Trans Inf Technol Biomed 16(3):454–462.
  23. Zouba N, Bremond F, Thonnat M (2009) Multisensor fusion for monitoring elderly activities at home. Comunicação apresentada em 6th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2009Google Scholar

Copyright information

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Pedro F. Pereira
    • 1
    Email author
  • Nuno M. M. Ramos
    • 1
  • João M. P. Q. Delgado
    • 2
  1. 1.CONSTRUCT-LFC, Faculty of EngineeringUniversity of PortoPortoPortugal
  2. 2.Department of Civil Engineering, Faculty of EngineeringUniversity of PortoPortoPortugal

Personalised recommendations