The literature emphasises the important role that occupants play regarding
the energy performance of buildings. Scholars have applied several methods to assess
occupants’ preferences and practices in their field studies. Technological innovations
such as Internet-of-Things (IoT) may capture valuable objective information that can
be translated into mathematical models. Such models are vital in Building Performance
Simulation (BPS) practices as they are expected to reduce performance gaps between
expected and real energy use in buildings during operational phase. However, datadriven
models strictly related to physical parameters exclude essential subjective
information like occupant preferences and needs. There is enough evidence showing
that individual differences impact on thermal preferences and levels of comfort
indoors, which must also be considered in occupant behaviour studies. Aside from
individual preferences, there is also social influence when occupants share spaces and
the control of building systems. Several methods commonly used in social science
studies are expected to incorporate the needed subjective information in this field if
properly used. Therefore, this chapter explores the potentials of combining objective
information gathered from technological innovations with subjective inputs obtained
through qualitative methods.
Keywords: Behavioural sensing, Building control, Building operation, Comfort,
Energy, Energy efficiency in buildings, Indoor environment, Internet of things,
Occupant behaviour, Social science, Technology.
