Our solution provides end-to-end service for farms starting from a Ground station which is a Web-based tool accessible across multiple devices to plan a mission in the region of interest in the agricultural field. Then optimized the path for the multiple UAVs to provide a power-efficient system. Each UAV was equipped with an onboard computer and camera to allowing them to collect image data. This Data was sent to our server which then uses a Deep Learning Algorithm called Convolution Neural Network to process and classify the collected data to their respective classes (either a healthy crop or diseases-affected crops/Weeds). The results of the analysis are present to the user on the web-based tool highlighting areas that are affected on the map in an easy-to-understand way. Both Simulation and field tests show that the architecture offers a number of advantages that include fault-tolerance, robustness, developer, and user-friendliness. Sectors Artificial intelligence, Crop farming, UAVs (drones) Location Addis Ababa, Ethiopia Stage Sign in to view details Markets Sign in to view details Customer model Sign in to view details Revenue Sign in to view details Contact Sign in to view details Social media