The presented study describes developing a method for observing building occupants’ activity. Once their activity is registered, such data can be used to identify typical patterns in their behaviour. The collected information will support development of an occupant-behaviour-energy-related model in residential buildings. Data registration was done with the use of the Microsoft Kinect device as a depth registration camera. This research explores an innovative approach to investigating residents’ living and working habits. It supports the already existing thermal comfort models by delivering high resolution information about occupants’ activities. The obtained solution and its output will be used in the next stage of developing a dynamic metabolic rate (D-MET) model that will simulate the MET value. With proper data, it will be possible to estimate the real impact of occupants and their behaviour on energy consumption of buildings.
Occupant sensing and data acquisition are essential elements for occupant behavior research. A wide range of different types of sensors has been implemented to collect rich information on occupants and their interactions with the built environment, such as presence, actions, power consumption, etc. This information establishes a foundation to study the physiological, psychological, and social aspects of occupant behavior. This chapter summarizes existing occupancy and occupant behavior sensing and data acquisition technologies in terms of field applications, and develops nine performance metrics for their evaluation. The reviewed technologies focus on both occupants’ presence and interactions with the built environment, and are grouped into six major categories: image-based, threshold and mechanical, motion sensing, radio-based, human-in-the-loop, and consumption sensing. This chapter provides an overview and discussion of different current state-of-the-art and future sensing technologies for researchers.
ZEN pilot project Zero Village Bergen. ©Bergen Municipality