Cluster analysis of microclimate data to optimize the number of sensors for the assessment of indoor environment within museums
For the first time, the cluster analysis (k-means) has been applied on long time series of temperature and relative humidity measurements to identify the thermo-hygrometric features in a museum. Based on ASHRAE (2011) classification, 84% of time all rooms in the Napoleonic Museum in Rome (case study) were found in the class of control B. This result was obtained by analyzing all recorded data in 10 rooms of the museum as well as using the cluster aggregation.