Carbon dioxide-based occupancy estimation using stochastic differential equations

Validation, optimisation and comparison of carbon dioxide-based occupancy estimation algorithms

“…Both methods are based on a CO 2 mass balance equation. Cal ı et al's method 8 uses a FOD, whereas the method of Wolf et al 21 uses SDE. The accuracy of the estimations is satisfactory and of the same magnitude for both Figure 12.…”

“…Furthermore, we intend to reduce the number of variables needed to run the simulation, e.g. by using predictive window opening models, such as the model developed by Markovic et al, 24 to estimate window opening instead of measuring it, to reach the same accuracies at low number of input variables as the model by Wolf et al 21 A limitation of this work is that we tested the two described models for office rooms exclusively. Testing the applicability for other room types and in particular, the influence of natural ventilation is left to future research.…”

“…Subsequently, the likelihood is maximised with respect to N occ to estimate the occupancy states. A more detailed description of the here described method can be found in Wolf et al 21 The estimation routine was implemented in the statistical computing software R.…”

“…This paper discusses an adjustment of the model of Cal ı et al 8 as discussed in Nienaber et al 20 and compares this adjusted model with one presented by of Wolf et al 21 First, we introduce both models, detailing their operating principles, including how we adjusted their parameters to run optimally with the given data set. Subsequently, we explain our methods for aggregating the data set, which both models used.…”

“…Wolf et al. 21 presented a grey-box model to estimate room occupancy. In contrast to the above-mentioned mass balance models, their approach employed a stochastic differential equation (SDE) to describe the CO 2 mass balance.…”