Placement of Package Delivery Center for UAVs with Machine Learning

Commercially available unmanned aerial vehicles (UAVs) are usually more affordable and feasible for easy deployment compared to military-level UAVs in civilian applications. However, having a bounded range limits the use of commercially available UAVs in package dropping scenarios. In this paper, we have generated a synthetic dataset for the scenario in which drones or UAVs are used to drop packages to two neighborhoods. The charging and package pick-up station is located between two neighborhoods. By leveraging the synthetic dataset, the location of the charging station is predicted by machine learning techniques given the package request frequency, package dropping times of the UAV, and targeted package delay for the neighborhoods. The results showed that deep neural networks and support vector regressor are more successful in deciding the charging station location.