Forest surveillance with artificial intelligence and digital technologies - FORSAID

• Forschungsstelle: SBFI
• Projektnummer: 24.00223

Abstract (Englisch)

Forests have an important role in the achievement of the objectives of the European Green Deal. Forest trees are increasingly threatenedby invasive pests, with many of them being regulated in the Union territory. FORSAID has as an overall goal to develop a comprehensivecombination of innovative digital technologies aimed at detecting regulated forest pests at an early stage, surveying their occurrencein the territory, and providing essential information for the adoption of phytosanitary measures to limit their spread and impacts. Theproject adopts a multi-actor and multidisciplinary approach tailored to develop and favour the adoption of digital technologies at differentspatial and temporal scales associated with a selected list of important regulated forest pests. The Internet of Things (IoT) will be used tocreate networks of insect traps for major guilds of insects, thanks to innovative deep learning analysis of images sent remotely from thetraps. Robotized devices will be developed and tested for the automatic barcoding of the captured pests. Drones equipped with sensorswill be used for the scanning of plant health status through the measure of physiological variables. Remote sensing techniques will beused to validate existing ground-truth data on the occurrence of tree alterations associated with abiotic and biotic factors, and modelsbased on Artificial Intelligence (AI) and machine learning (ML) will be developed to discriminate different types of stresses as soon asthey appear. An economic analysis will address the costs and benefits of using digital technologies for the detection and surveillancemeasures, considering the economic, environmental, and social impacts of regulated pests in EU forests. Stakeholders from the forestsector will be involved in a multi-actor approach to drive the research to applicable results and co-construct guidelines for the best useof new digital technologies for forest pest detection and monitoring.