User behaviour has a significant contribution to the final energy consumption figures of buildings. As indicated in finding from the IEA EBC Annex 66 project, proper and continuous monitoring of occupant behaviour inside buildings can support reaching of the zero energy-building standard (ZEB). The collected data, however, must be gathered via in situ methodology to avoid potential influences on data quality. Commonly used measurement techniques such as plug-load monitoring, CO2 level sensing or PIR, are sufficient to describe energy-related occupant behaviour at the zone/room level. However, this resolution of description can only be treated as an energy consumption overview as it cannot guarantee an identification of individual indoor environment quality preferences. Development of a solution that can grant access to an individual description of occupant needs requires direct monitoring of their inside building activity. Herein, access to necessary input data can be provided with the use of the depth registration camera because the suggested measuring technique can deliver information about routine occupant positioning inside each zone/room. Additionally, it provides data about the position of the observed occupants' body limbs. If information about the distribution of the occupants is delivered, it is possible to couple such with a result matrix obtained via CFD studies. Moreover, the coordinates of occupant limb positions can be used as a data-probing device in simulation studies. With such a tool, it will be possible to monitor the exposure of each limb to the thermal properties of indoor air. Collecting data through this methodology can grant access to a more profound understanding of the occupant thermal comfort sensation and the habits that influence building energy use.
[1]
Tianzhen Hong,et al.
Occupant behavior modeling for building performance simulation: Current state and future challenges
,
2015
.
[2]
P. O. Fanger.
Thermal comfort : Analysis and applications
,
1972
.
[3]
Yan Da,et al.
Indoor occupant behaviour monitoring with the use of a depth registration camera
,
2019,
Building and Environment.
[4]
Andreas Wagner,et al.
Exploring occupant behavior in buildings: Methods and challenges
,
2018
.
[5]
Amar Aganovic.
Airflow distribution for minimizing human exposure to airborne contaminants in healthcare facilities
,
2019
.
[6]
Mehrdad Rabani,et al.
Numerical analysis of airflow around a passenger train entering the tunnel
,
2015
.
[7]
E. Halawa,et al.
The adaptive approach to thermal comfort: A critical overview
,
2012
.
[8]
Yuan Jin,et al.
Modeling occupancy and behavior for better building design and operation—A critical review
,
2018,
Building Simulation.
[9]
Ken Parsons,et al.
Human Thermal Environments: The Effects of Hot, Moderate, and Cold Environments on Human Health, Comfort and Performance
,
1999
.
[10]
C. Coskun.
A novel approach to degree-hour calculation: Indoor and outdoor reference temperature based degree-hour calculation
,
2010
.
[11]
Roberto Lamberts,et al.
A review of occupant behaviour in residential buildings
,
2018,
Energy and Buildings.