TY - JOUR
T1 - An Amateur Drone Surveillance System Based on the Cognitive Internet of Things
AU - Ding, Guoru
AU - Wu, Qihui
AU - Zhang, Linyuan
AU - Lin, Yun
AU - Tsiftsis, Theodoros A.
AU - Yao, Yu Dong
N1 - Publisher Copyright:
© 1979-2012 IEEE.
PY - 2018/1
Y1 - 2018/1
N2 - Drones, also known as mini-unmanned aerial vehicles, have attracted increasing attention due to their boundless applications in communications, photography, agriculture, surveillance, and numerous public services. However, the deployment of amateur drones poses various safety, security, and privacy threats. To cope with these challenges, amateur drone surveillance has become a very important but largely unexplored topic. In this article, we first present a brief survey to show the stateof-the-art studies on amateur drone surveillance. Then we propose a vision, named Dragnet, tailoring the recently emerging Cognitive Internet of Things framework for amateur drone surveillance. Next, we discuss the key enabling techniques for Dragnet in detail, accompanied by the technical challenges and open issues. Furthermore, we provide an exemplary case study on the detection and classification of authorized and unauthorized amateur drones, where, for example, an important event is being held and only authorized drones are allowed to fly over.
AB - Drones, also known as mini-unmanned aerial vehicles, have attracted increasing attention due to their boundless applications in communications, photography, agriculture, surveillance, and numerous public services. However, the deployment of amateur drones poses various safety, security, and privacy threats. To cope with these challenges, amateur drone surveillance has become a very important but largely unexplored topic. In this article, we first present a brief survey to show the stateof-the-art studies on amateur drone surveillance. Then we propose a vision, named Dragnet, tailoring the recently emerging Cognitive Internet of Things framework for amateur drone surveillance. Next, we discuss the key enabling techniques for Dragnet in detail, accompanied by the technical challenges and open issues. Furthermore, we provide an exemplary case study on the detection and classification of authorized and unauthorized amateur drones, where, for example, an important event is being held and only authorized drones are allowed to fly over.
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U2 - 10.1109/MCOM.2017.1700452
DO - 10.1109/MCOM.2017.1700452
M3 - Article
AN - SCOPUS:85040739915
SN - 0163-6804
VL - 56
SP - 29
EP - 35
JO - IEEE Communications Magazine
JF - IEEE Communications Magazine
IS - 1
M1 - 8255734
ER -