Bois noir (BN) is a cicada-borne grapevine disease first observed to have entered Switzerland in the 1990s, now causing up to 50% loss of yield and vines in vineyards. It is associated with the phytoplasma Candidatus Phytoplasma solani (16SrXII-A), transferred from host plants common in vineyard ground cover, to grapevines (Vitis vinifera), by the planthopper Hyalesthes obsoletus Signoret (Hemiptera: Cixiidae). Diseased plants cannot be cured, and climate change-related temperature anomalies increase infection risk. In Switzerland, BN is a “regulated non-quarantine organism”, a classification for “particularly dangerous plant pathogens and pests which are already widely distributed”. Because there are no options for direct control of BN, practical methods for systematic and early detection are urgently needed to support management and prevention. Such methods will also be useful in preventing other invasive cicada-borne grapevine diseases, such as the mandatory quarantine disease flavescence dorée, whose emergence in BN-infected areas is threatening vineyards. The goal of the study is to develop a smart package of innovative monitoring and prevention methods. Detection approaches will use spectral imaging and sampling of plant volatiles related to BN-disease infection. The data will be combined to train machine learning models to categorize diseased vines and indicate discriminating features, and simplified automated detection strategies will be developed. The package is developed in a transdisciplinary, co-creative, step-by-step process with winegrowers, representatives of the wine industry, and governmental plant quarantine service experts. The project started in July 2023. Here, we discuss insights from the initial field season, and future plans.