Method for long-term mapping of occupancy patterns in open-plan and single office spaces by using passive-infrared (PIR) sensors mounted below desks

Occupancy is a key input variable for sizing heating, ventilation and air-conditioning (HVAC) in buildings. However, HVAC designers typically estimate occupancy data based on assumptions which rarely reflect the actual situation. Consequently, these assumptions might lead to underor oversized HVAC systems that either provide too low or too high peak loads or ventilation airflows than actually required to satisfy indoor environmental quality (IEQ) requirements during building operation. To address these issues, existing studies suggest various methods for collecting and analysing occupancy, however mostly in single office spaces or atan overall building level. The objective of the present study was to evaluate the suitability of using passive-infrared (PIR) sensors mounted below occupants' desks for collecting long-term occupancy data in open-plan and single office spaces. The method was tested in two office buildings for seven months. It determined occupant presence and count with an accuracy of 87.5% compared to manual observations. Furthermore, the study demonstrated that occupancy data could be used to (1) generate occupancy schedules for input in building simulation models, (2) potentially reduce design ventilation airflows for HVAC sizing and (3) evaluate decisions to change the office space layout (e.g. number of desks) for more efficient space-use. (C) 2020 Elsevier B.V. All rights reserved.

Automated summary

The study evaluated the use of passive-infrared sensors for collecting long-term occupancy data, achieving an accuracy of 87.5% compared to manual observations. The gathered occupancy data can be used to generate occupancy schedules for building simulation models, potentially reduce design ventilation airflows for HVAC sizing, and evaluate decisions to change office space layouts for more efficient space-use.