Active & intelligent PAckaging materials and display cases as a tool for preventive conservation of Cultural Heritage (APACHE)

Forskningsprojekt, 2019 – 2022

Most Cultural Heritage objects housed by museums are often stored under unsuitable climate conditions. APACHE will develop a cutting edge technology to control and prevent the degradation of such patrimony. The novel approach is based on three pillars: 1) advanced sensing and absorbing materials to control the artifacts’ environment; 2) modeling to define the threshold of artifacts’ degradation and to discriminate between the need for preventive or
remedial conservation; 3) remote control of the works of art stressors. The unique combination of these pillars will reduce to the lowest possible level the costs actually required by conventional technology for art conservation. New generation of active and intelligent display cases, crates, and storage boxes, will be implemented thanks to: i)

Theunique APACHE partnership, comprising the most important experts in the three aforementioned pillars; ii) The
development of easy-to-use sensing devices able to communicate through Wireless Sensor Networks and Radio Frequency Identification Devices thanks to Industry 4.0-5.0 ICT technologies, granting the optimal environmental conditions around the art objects. Multiscale models integrated in an open simulation environment will be used to predict the degradation of artefacts and set the properties of sensors (detection limits) and polyfunctional absorbents. APACHE includes small, medium, and large museums exhibiting representative variety of display and storage conditions. For instance, the Venice Peggy Guggenheim Collection features one of the most important collections of modern/contemporary art, which experiences highly unfavorable environmental conditions, difficult to control with conventional tools. Centre Pompidou and National Museum of Hungary possess a vast amount of artefacts stored in deposits (e.g. in crates and boxes). Moreover, a decision-making tool composed by a modular set of decision trees will be offered to end-users to guide them through the best solutions.