With the primary goal of enhancing the efficiency of drones for research and rescue missions through the exploitation of neuromorphic sensors and event-based vision, our focus in this work lies in setting up a simulated environment that can be used for synthetic data generation. In particular, we employ Unreal Engine to generate scenes suitable for the case of vehicle perception, followed by a dynamic event-based simulation environment in conjunction with AirSim and v2e tools. The synthetic event data acquired in this simulated environment serves as a crucial resource for training Artificial Intelligence (AI) systems, with a specific focus on car detection using YOLOv7.