Research on Sugarcane Pest and Disease Monitoring System Based on Unmanned Aerial Vehicle Remote Sensing

As agriculture continues to develop, the cultivation area of sugarcane has been expanding steadily. Traditional agricultural management techniques are facing limitations such as restricted manual inspection range, high time consumption, low accuracy in pest and disease identification, crude control methods, and heavy labor intensity. This study aims to monitor sugarcane pests and diseases using unmanned aerial vehicle (UAV) remote sensing. By collecting precise information during periods when sugarcane is highly susceptible to pests and diseases, and employing neural networks for real-time diagnosis, we aim to facilitate sugarcane farmers in accurately identifying and controlling pests and diseases. This will mitigate the harm caused by pests and diseases, leading to increased sugarcane yield and economic benefits.