Integrated and Predictive Systems for Preventive Conservation. (1st August 2018)

• Record Type: Journal Article
• Authors: Calabrese, Matteo; Odisio, Nicoletta; Appolonia, Lorenzo; Bernagozzi, Andrea; Christille, Jean Marc; Glarey, Annie; Migliorini, Simonetta; Seris, Nicole
• Is Part Of: Studies in conservation. Volume 63(2018)Supplement 1
• Page Start: 43
• Page End: 50
• Publication Date: 2018-08-01
• Subjects: Preventive conservation -- climatic data -- machine learning -- virtual sensors -- environmental monitoring -- arch of augustus; Art objects -- Conservation and restoration -- Periodicals; 700.288
• DOI: 10.1080/00393630.2018.1504436
• Languages: English
• ISSNs: 0039-3630

Abstract

ABSTRACT : Forecasting the dynamics of alteration in materials, in particular the timescale of degradation, is relevant to preventive conservation, and great deal of effort has gone into developing new models for the kinetics of physical and chemical phenomena affecting materials. Creating monitoring systems able to assess the evolution of degradation processes that inform intervention programs is necessary to ensure the protection of historical and artistic heritage. The Research Unit for Integrated and Predictive Systems (SIP) is presented: it develops new tools and algorithms to study the alteration of materials using non-invasive techniques and passive monitoring, as well as new mathematical models to predict how the surfaces of materials degrade with time. The paper focuses on the Arch of Augustus and presents initial results from two virtual sensors used to 'monitor' environmental conditions outdoors. These systems do not need a permanent, invasive network of sensors in situ . They rely instead on local infrastructure for measuring air quality, and adopt smart information fusion algorithms to predict the environment around the cultural heritage site. Virtual sensors can provide an effective control system that highlights specific conditions linked to specific forms of alteration.