A C4 Software for Anti-Drone System

Abstract

Mini unmanned aerial vehicles (UAVs), commonly known as small drones, have seen outstanding advancements in recent years and have been used in a variety of fields. However, their potential misuse for illegal activities and the risks they pose to safety and privacy have raised concerns. To address these issues, we propose a Command, Control, Communications, and Computers (C4) software able to manage and control anti-drone systems. Our software solution includes an easy-to-use dashboard that processes and displays video data from surveillance sensors. It incorporates AI-powered functionalities, including object detection, target tracking, and classification of small drones. At the inference stage, the network models for drone detection and classification functionalities have achieved an accuracy exceeding 96 %. We have evaluated the effectiveness of our solution by deploying it in a no-fly zone, where it successfully identified and tracked drones in near real-time. The proposed control system provides unified information with which the entire anti-drone process can be managed starting from the detection of each threat.

Keywords: Mini-UAV; Anti-drone; Data analytics; Dashboard; Deep learning; C4

Description