Fungi in museums and collections: a novel, highly sensitive, AI powered sensor system for the early stage detection of fungal contaminations

Fungal infestation is one of the greatest dangers for art and cultural artefacts in museums, collections and archives. Fungi damage materials by decomposition, corrosion and aesthetical changes and they are posing a health risk for museum staff and visitors. Fungal infestation is predicted to increase significantly in regions above 50° latitude in the coming decades due to more rainfall and higher temperatures as a consequence of climate change. The situation is made worse by the urgent requirement for museums to become more climate-efficient and to use less energy for air conditioning. Based on this, the timely detection of fungal infestation is an increasingly important issue. There is a need for a simple, reliable, highly sensitive method for the early detection of mould growth in museums, collections and depots. Therefore, we suggest to develop a novel metal-sensor system with 'artificial intelligence' to detect the smell (volatile organic compounds) that mould produce during growth. This technology could enable a 'real-time' determination of volatile mould emissions as marker for fungal growth with some conclusions on the type of mould and even the type of material infested. In this project it is planned to adapt and optimize an easy-to-install and low-cost system with high sensitivity for use in museums and collections. The research will be done in collaboration with partner museums in Austria with the aim to make the system available for all interested heritage collections.