Paper Info
Title
A Statistical Approach for A-Posteriori Deployment of Microclimate Sensors in Museums: A Case Study
Abstract
The deployment of sensors is the first issue encountered when microclimate monitoring is planned in spaces devoted to the conservation of artworks. Sometimes, the first decision regarding the position of sensors may not be suitable for characterising the microclimate close to climate-sensitive artworks or should be revised in light of new circumstances. This paper fits into this context by proposing a rational approach for a posteriori deployment of microclimate sensors in museums where long-term temperature and relative humidity observations were available (here, the Rosenborg Castle, Copenhagen, Denmark). Different statistical tools such as box-and-whisker plots, principal component analysis (PCA) and cluster analysis (CA) were used to identify microclimate patterns, i.e., similarities of indoor air conditions among rooms. Box-and-whisker plots allowed us to clearly identify one microclimate pattern in two adjoining rooms located in the basement. Multivariate methods (PCA and CA) enabled us to identify further microclimate patterns by grouping not only adjoining rooms but also rooms located on different floors. Based on these outcomes, new configurations about the deployment of sensors were proposed aimed at avoiding redundant sensors and collecting microclimate observations in other sensitive locations of this museum.
Year
DOI
Venue
2022
10.3390/s22124547
SENSORS
Keywords
DocType
Volume
museum, microclimate, multivariate approach, principal component analysis, cluster analysis, sensors, deployment, temperature, relative humidity
Journal
22
Issue
ISSN
Citations 
12
1424-8220
0
PageRank 
References 
Authors
0.34
0
8
Name
Order
Citations
PageRank
Francesca Frasca100.34
Elena Verticchio200.34
Paloma Merello300.34
Manuel Zarzo4256.01
Andreas Grinde500.68
Eugenio Fazio600.68
Fernando-Juan García-Diego700.34
Anna Maria Siani801.01