Data Driven Crop Disease Modeling

This article discusses the use of artificial intelligence and machine learning in precision farming, specifically in predicting crop diseases. The research focuses on developing data-driven methodologies and optimization approaches for building accurate disease models. Two studies were conducted to evaluate the suitability of social media and remote sensing data as alternative sources of information. The results show that while social media is not yet a viable option, vegetation indices from remote sensing can provide valuable insights.