Smart Heritage Artfacts 


Acromym Smart Heritage Artfacts
Project title  Smart Heritage Artfacts
Project strand
H2020 Innovative and affordable solutions for the preventive conservation of cultural heritage (IA),
Coordinating institution Fundación Santa Maria la Real del Patrimonio Histórico (Spain)



Participant countries
Fundación Santa Maria la Real del Patrimonio Histórico (Spain), GAIA-heritage (Lebanon), Fundación Cartif 8Spain), Instituto tecnologico metalmeccanico, mueble, madera, embalaje y afinesaidimme (Spain), Holonix srl, spin-off politecnico di Milano (Italy), Uninova, Instituto de desenvolvimiento de novas tecnologías Associacao (Portugal), Vertec h Group (France), Posavski Muzej Brezice (Slovenia), Real Academia de Bellas Artes de San Fernando (Spain), Este Sojamuuseum kindral laidoneri Muuseum (Finland), Teknologian tutkimuskeskus VTT Oy (Finland), Fratelli Piacenza (Italy), Slovak National Library (Slovacchia), Meta Group srl (Italy), Regional History Museum "Academician Yordan Ivanov" town of Kyustendil (Bulgaria), Institute for the Protection of Cultural Heritage of Slovenia (Slovenia), Palazzo Spinelli Associazione (Italy).
Subject area(s)
Heritage and Artcrafts
Abstract TSH ARTEFACT is based on the concept that ICT (Internet of Things, sensors, Intelligential Artificial and web based solutions) can help conservators, curators and museum managers to improve their tasks and offer better public services in a cost efficient way.
Project objectives SH ARTEFACTS will develop an innovative, low-cost, modular and scalable tool that helps to pilot effective and efficient measures of PC in SMM. It starts from an already existing and Cultural Heritage (CH) monitoring technology, integrated and combined with open source implementation of emerging modular IT technologies. The solution will consist of a platform that includes a monitoring system for CH artefacts and environmental conditions, a multi-scale modelling module to simulate material behavior, and predictive and decision support modules with implemented algorithms to define PC actions in function of collected and historical data. An economic module will combine in real time technical data, prediction and cost analysis to support the PC strategies.