A Novel Deep Learning Framework Integrating UAV Hyperspectral Imagery and IoT Sensor Data for Real-Time Nitrogen Deficiency Detection in Wheat

research introduces a cutting-edge deep learning framework that combines UAV-based hyperspectral imagery with IoT sensor data to detect and map nitrogen deficiency in wheat crops in real time. By fusing detailed spectral data with continuous environmental and soil metrics, the system enables non-invasive, high-resolution monitoring of crop nitrogen status. This hybrid approach supports precise, variable-rate fertilizer application, improving yield and quality while minimizing environmental impact. The solution marks a significant step toward sustainable, data-driven Agriculture 5.0.