Research on an intelligent rice crop monitoring system based on UAV optical remote sensing and AI

Abstract

According to the study designed and impIemented an intelligent rice crop monitoring system based on unmanned aerial vehicle (UAV) optical remote sensing, and artificial intelligence (AI) technology. A multirotor UAV platform, multispectral imaging sensors, edge computing modules and a cloud-based AI analysis platform are integrated into the system, which serves to realize real-time, non-destructive and large-area monitoring of key rice growth stages. Specific monitoring dimensions cover the crop’s growth status, nutritional condition, pest and disease occurrence as well as water stress level, all of which are core indicators for assessing rice growth dynamics in field production. We used computer models to look at pictures of the rice from the air. These models are good at looking at pictures from altitudes. We were able to get a good look, at the pictures of the rice and figure out what was going on with the rice crops. We could even tell what was going on with the features of the rice. Field comparative experiments demonstrated that the system performs excellently in leaf area index (LAI) inversion accuracy (R²=0.91), nitrogen content estimation (RMSE=0.25%), and early identification of rice blast (F1-score=0.89), providing an efficient and reliable technical tool for precision agriculture management.