Audio-based classification of drones – AuDroK
© Fraunhofer IVI
Drones are operated more and more frequently. This has advantages, but it also causes risks and dangers for other aircraft, infrastructures and third parties. To minimize these risks, government-provided legal guidelines are needed, and their implementation requires effective detection and classification technology. A very well-suited and economical technology for this purpose is analyzing drone sounds with the help of machine learning algorithms. The aim of the AuDroK Project is to compile a dataset containing the sounds of different drone models and to develop classifiers that allow the identification of drones based on their sounds. The project will end with a model experiment for assessing the performance of the approaches developed. The project's successful completion will mean a contribution to improving the safety of drone flights and facilitating the integration of drones into our society.