Proposed Fuzzy-Stranded-Neural Network Model That Utilizes IoT Plant-Level Sensory Monitoring and Distributed Services for the Early Detection of Downy Mildew in Viticulture
Novel monitoring architecture approaches are required to detect viticulture diseases early.Existing micro-climate decision support systems can only cope with late detection from empirical and semi-empirical models that provide less accurate results.Such models cannot alleviate precision viticulture planning and pesticide control actions, providing