The ubiquitous utility of drones can lead to technical, security, and public safety issues that need to be addressed, regulated and prevented, e.g. spying, transfer of illegal or dangerous goods, disturbing electricity and telephone lines, and assault. Therefore, security agencies are in continuous search for technologies and intelligent systems (commonly called anti-drone systems) that are capable of detecting and possibly identifying drones using different modalities and techniques such as radio frequency (RF)-based, or video-based detection.
The smart IoT systems research group (SIoTS-RG) in collaboration with security agencies in Qatar tackle challenges related to anti-drone systems, including machine learning for RF-based, and Video-based drone detection and identification, in addition to designing smart jamming techniques to neutralize illegitimate drones for public safety and security applications.
RF-based detection and identification
Drone video-based detection and tracking
Smart drone jamming
RF-based detection and identification using machine learning
WiFi-based drone detection and identification
Drone video-based detection and tracking using machine learning
Drone shooter: smart drone jamming