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.
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Acknowledgments
The authors are grateful to the Museo Napoleonico staff for their assistance and, in particular, to Dr. Fabio Benedettucci for his valuable support. We also thank Climate Consulting S.r.l. for providing the meteorological data.
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All authors have helped to develop the paper. A.M.S. has played the major role supervising and coordinating the whole work, A.M.S. and F.F. have equally contributed in the conceptualization and writing the paper, M.D.M. and V.B. have performed the measuring campaigns in the museums, A.M.S. has supervised the statistical elaboration of climatic data, F.F. and M.D.M. have equally contributed in the statistical elaboration of the experimental data, and E.F. has contributed in the statistical elaboration of the data and coordinated the manuscript preparation.
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Responsible editor: Constantini Samara
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Siani, A.M., Frasca, F., Di Michele, M. et al. Cluster analysis of microclimate data to optimize the number of sensors for the assessment of indoor environment within museums. Environ Sci Pollut Res 25, 28787–28797 (2018). https://doi.org/10.1007/s11356-018-2021-3
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DOI: https://doi.org/10.1007/s11356-018-2021-3