The accuracy of reading sensor depends on the operation range and the reliability level of sensor; therefore, uncertainty cannot be avoided. This study is proposed to assess the uncertainty of a CO₂ reading sensor during estimating the occupancy dis...
The accuracy of reading sensor depends on the operation range and the reliability level of sensor; therefore, uncertainty cannot be avoided. This study is proposed to assess the uncertainty of a CO₂ reading sensor during estimating the occupancy distribution in office multi-room buildings. Bayesian Markov Chain Monte Carlo approach used to calculate the occupancy in the individual space based on CO₂ information. CONTAM was used to generate CO₂ concentration from given information of occupancy schedule, building model and ventilation rate in each room. Noise levels were added into CO₂ data to investigate an acceptable uncertainty in the occupancy estimation.