TY - JOUR
T1 - Energy intelligent buildings based on user activity
T2 - A survey
AU - Nguyen, Tuan Anh
AU - Aiello, Marco
N1 - Relation: http://www.rug.nl/research/cbn/
Rights: University of Groningen, Johann Bernoulli Institute for Mathematics and Computer Science
PY - 2013/1
Y1 - 2013/1
N2 - Occupant presence and behaviour in buildings has been shown to have large impact on heating, cooling and ventilation demand, energy consumption of lighting and appliances, and building controls. Energy-unaware behaviour can add one-third to a building's designed energy performance. Consequently, user activity and behaviour is considered as a key element and has long been used for control of various devices such as artificial light, heating, ventilation, and air conditioning. However, how are user activity and behaviour taken into account? What are the most valuable activities or behaviours and what is their impact on energy saving potential? In order to answer these questions, we provide a novel survey of prominent international intelligent buildings research efforts with the theme of energy saving and user activity recognition. We devise new metrics to compare the existing studies. Through the survey, we determine the most valuable activities and behaviours and their impact on energy saving potential for each of the three main subsystems, i.e., HVAC, light, and plug loads. The most promising and appropriate activity recognition technologies and approaches are discussed thus allowing us to conclude with principles and perspectives for energy intelligent buildings based on user activity. (c) 2012 Elsevier B.V. All rights reserved.
AB - Occupant presence and behaviour in buildings has been shown to have large impact on heating, cooling and ventilation demand, energy consumption of lighting and appliances, and building controls. Energy-unaware behaviour can add one-third to a building's designed energy performance. Consequently, user activity and behaviour is considered as a key element and has long been used for control of various devices such as artificial light, heating, ventilation, and air conditioning. However, how are user activity and behaviour taken into account? What are the most valuable activities or behaviours and what is their impact on energy saving potential? In order to answer these questions, we provide a novel survey of prominent international intelligent buildings research efforts with the theme of energy saving and user activity recognition. We devise new metrics to compare the existing studies. Through the survey, we determine the most valuable activities and behaviours and their impact on energy saving potential for each of the three main subsystems, i.e., HVAC, light, and plug loads. The most promising and appropriate activity recognition technologies and approaches are discussed thus allowing us to conclude with principles and perspectives for energy intelligent buildings based on user activity. (c) 2012 Elsevier B.V. All rights reserved.
KW - Building automation
KW - Energy awareness
KW - Activity recognition
KW - OFFICE BUILDINGS
KW - EMBEDDED AGENTS
KW - CONSUMPTION
KW - NETWORKS
U2 - 10.1016/j.enbuild.2012.09.005
DO - 10.1016/j.enbuild.2012.09.005
M3 - Review article
SN - 0378-7788
VL - 56
SP - 244
EP - 257
JO - Energy and buildings
JF - Energy and buildings
ER -