CO2 experimental measurements towards the development of a predictive framework using user actions in smart buildings

A transition towards smart buildings is one of the challenges of the 21st century. To achieve this goal, the use of smart sensors and smart appliances can be crucial. Although research about linking real-time monitoring and the operation mode of building appliances have been carried out by other researchers, the focus was on the energy performance relegating indoor air quality and thermal comfort to the background. This paper focuses on the analysis of the preliminary results on experiments performed in a real test room to evaluate the CO2 distribution within a single zone. The strategy is to include the concerns regarding indoor air quality in a global framework where weather forecast, users' actions and building simulation will be combined in a real-time predictive methodology. The experiments included the evaluation of the air change rate using metabolic-related CO2 as tracer gas into the test room. The attained results show an average air change rate value of 0.55h−1. Moreover, the variability of the CO2 concentration throughout the space was also analysed for different positions, using CO2 data loggers calibrated as the reference and real-time sensors. It was concluded that no optimal position of sensors was observed for a single zone, due to the small swing attained for different sensors positions.