On-device Crop Disease Prediction: A realistic case for vineyards

Internet of Things (IoT) is one of the next big concepts to support societal changes and economic growth, with the help of Artificial Intelligence and edge computing. A whole new range of applications that leverage data and metadata from connected IoT devices provide novel human-centric services in areas such as smart agriculture. In this paper, we investigate the efficiency of executing ML-based crop disease prediction on a commercial drone device and demonstrate its potential in vineyards. We conduct inference of the trained models on several IoT and edge devices’ processors and demonstrate the potential for real-time decision-making and therefore enabling targeted treatment for affected areas for optimizing crop protection strategies