UAV-based Maize Disease Monitoring: Integrating Physical Model and Machine Learning

This PhD research uses drone technology to better protect corn crops from devastating diseases. Finding sick plants early is traditionally difficult. To solve this, we equipped drones with advanced cameras that capture light beyond human vision, allowing us to monitor maize health from the sky. The core innovation combines artificial intelligence (AI) with computer simulations of how plants reflect light. This approach led to two major breakthroughs: a new tool for spotting diseases much earlier than human observation, and a predictive model that acts like a "weather forecast" for crop infections, anticipating exactly where and when disease will spread across a field. For agriculture, these early-warning systems are game-changing. They empower farmers to intervene before crops are severely damaged. Ultimately, this research drives smarter precision farming, helping secure global food production and minimize losses.