Gajanan Ankatwar
Machine Learning
August 2024
UAVs outfitted with remote sensing technologies present valuable options for detecting crop diseases in precision agriculture. reviewed the application of ML and DL techniques in conjunction with UAV-based remote sensing to improve the accuracy of crop disease identification. UAVs offer versatile coverage of agricultural fields and capture high-resolution images, which aid in the automated detection of diseases across various types of crops. UAVs gather data on crop features to assess disease levels by utilizing RGB, multispectral, and hyperspectral sensors. Earlier research has focused on using vegetation indices and extracting data at the plot level for disease evaluation. Recent advancements in UAV technology and sensor capabilities have made it possible to use ML & DL algorithms for more precise illness estimation. This paper assesses the benefits and drawbacks of current methods and highlights the significance of a thorough investigation of ML and DL techniques for agricultural disease detection with unmanned aerial vehicles (UAVs). The combination of UAV-based remote sensing with sophisticated data-driven techniques has the potential to significantly improve early disease detection, assist farmers in making timely decisions, and minimize yield losses in precision agriculture
446- 492
© Airo Journals 2021
