Ventilation rate and occupancy estimation in an office building

Smart or Intelligent buildings are becoming the industry standard. The Building Information Modeling (BIM) and its most recent development, the Digital Twin... [ view full abstract ]

Smart or Intelligent buildings are becoming the industry standard. The Building Information Modeling (BIM) and its most recent development, the Digital Twin Technology (DTT) are giving access to an always increasing amount of data.

Though the quantity of information about a building is plentiful, its access is still restricted but most importantly, its use during the whole life cycle of the building is highly undermined. Added value and new services could result from an improved management of buildings data.

In this research, Indoor Air Quality (IAQ) data is used to extract precious information from two Finnish offices: the ventilation rate and the occupancy. Cheap and reliable sensor technology is used to gather continuous carbon dioxide (CO2) measurements. The mass balance model is then applied to the data to model the air exchange between outdoor and indoor air. Parameters of the mass balance model is estimated using Bayesian statistics methods. Finally, the results are compared to guidelines and recommendations in order to assess the performance and health of the measured spaces.

This methodology highlights several advantages from a better usage of continuous IAQ data like a non-intrusive method for occupancy analysis or real-life performance versus theoretical performance of the ventilation rate. Those extracted building characteristics are essential to assess the performance and health of the indoor environment and to maximize health and satisfaction from occupants.