The aim of this paper is to evaluate the efficacy of the Digital Twin approach to achieving Sentient buildings able to develop preservation and conservation action plans from environmental data. The case study is based on the integration of an H-BIM model with an AI-based Decision Support System implementing Machine Learning techniques for conserving museum collections in historical buildings.
From Cognitive to the Sentient Building. Machine Learning for the preservation of museum collections in historical architecture.
Federico Mario La Russa
;Cettina Santagati
2020-01-01
Abstract
The aim of this paper is to evaluate the efficacy of the Digital Twin approach to achieving Sentient buildings able to develop preservation and conservation action plans from environmental data. The case study is based on the integration of an H-BIM model with an AI-based Decision Support System implementing Machine Learning techniques for conserving museum collections in historical buildings.File in questo prodotto:
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