Technology like wireless sensor networks, cloud computing, artificial intelligence, big data analytics, and the internet of things can be used to make farming smarter (IoT). Some of the things that make smart farming work are field/crop management, irrigation control, water management, and nutrient management. Unmanned aerial vehicles (UAVs) make it possible to keep an eye on fields and crops without harming the environment. In conjunction with crop management and field analysis, drones measure things like chlorophyll content, leaf variation index, and vegetation index to decide if a plant or land is healthy. The proposed method is meant to lead to a drone that is accurate, cheap, and useful for many things. The way a camera takes pictures and how well it does it are always looked at and used in design to make quick and accurate decisions. Also, the images from the sensors are processed with models of artificial neural networks to improve how well the system works. By giving the drone intelligence, the spraying task can be done by itself. The proposed intelligent model is tested against the most popular artificial neural network (ANN) algorithms like naive bayes, K- nearest neighbor (KNN), support vector machine (SVM), decision tree, and random forest

Agricultural Drones; Artificial Intelligence; Internet of Things (IoT); Precision Agriculture; Wireless Sensor Networks.