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

Author(s)	Mr. Ravi Prakash Jaiswal, Manish Saraf, Vijendra Pratap Singh, Ambuj Kumar Misra
Country	India
Abstract	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.
Keywords	UAV-based hyperspectral imaging, IoT sensor networks, Deep learning data fusion, Nitrogen deficiency detection, Real-time nutrient mapping
Field	Computer Applications
Published In	Volume 16, Issue 3, July-September 2025
Published On	2025-09-28
DOI	https://doi.org/10.71097/IJSAT.v16.i3.8400
Short DOI	https://doi.org/g949wq

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