Cluster analysis of microclimate data to optimize the number of sensors for the assessment of indoor environment within museums

Abstract

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. The use of objective-oriented methodology allows to achieve an acceptable knowledge of the microclimate in case of multi-room buildings, reducing computations with large amounts of collected data and time-consuming in redundant elaborations. The cluster analysis enables to reduce the number of the sensors in microclimate monitoring programs within museums, provided that the representativeness of the instrument location is known, and professional conservators have assessed that the artifacts are well preserved.