Key points are not available for this paper at this time.
This paper introduces an innovative smart agriculture system aimed at enhancing farming efficiency, resulting in increased crop yields, reduced resource consumption, and minimized environmental impact. The proposed system integrates Recurrent Neural Networks (RNN) and edge computing within precision agriculture, leveraging the synergy of IoT drones and sensor fusion. By combining data from various sensors mounted on drones, including multispectral cameras and LiDAR, with ground based IoT devices such as pH sensors, soil moisture sensors, and temperature and humidity sensors, a comprehensive understanding of crop health, soil conditions, and environmental factors is achieved.
Soultane et al. (Wed,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: