Cerberus Concept

Pest monitoring is both necessary and very challenging. It is typically performed through costly and time-consuming field visits to count and identify pests in fixed traps, resulting in limited spatial and temporal resolution. Consequently, there is an urgent need for cost-effective approaches to detect and discriminate pest incidence at large spatial scales and within reasonable timeframes. Cerberus will capitalize on early detection to reduce pesticide use and intelligent spray applications to sustainably eradicate pests at their early stages, when damage is reduced and the impact of treatments is high even with low spray rates. To do so, Cerberus will combine large-scale crop observation models enhanced by the high revisiting time and diversity of bands offered by Copernicus, with the high reliability of proximal sensing granted by IoT insect traps reporting at a daily basis, robot-based monitoring at less than 1 m from the crops, and the granularity resulting from citizen data using dedicated apps. Data coming from multiple sources will be merged through a cloud platform, which will produce risk maps and spraying recommendations for users by applying AI algorithms.