We are developing new methods to monitor and track drones while they are in flight.

The growing use of drones has places an increasing need on technologies to accurately monitor and characterise such vehicles. We have recently developed a CNN using a decision tree and ensemble structure to fully characterise drones in flight. Our system determines the drone type, orientation (in terms of pitch, roll, and yaw), and performs segmentation to classify different body parts (engines, body, and camera).

Read more about this work in our IEEE paper: DroneSense: The Identification, Segmentation, and Orientation Detection of Drones via Neural Networks