Audio-Based Drone Detection and Identification Using Deep Learning Techniques with Dataset Enhancement through Generative Adversarial Networks
Date
2021-08-01Metadata
Show full item recordAbstract
Drones are becoming increasingly popular not only for recreational purposes but in day-to-day applications in engineering, medicine, logistics, security and others. In addition to their useful applications, an alarming concern in regard to the physical infrastructure security, safety and privacy has arisen due to the potential of their use in malicious activities. To address this problem, we propose a novel solution that automates the drone detection and identification processes using a drone’s acoustic features with different deep learning algorithms. However, the lack of acoustic drone datasets hinders the ability to implement an effective solution. In this paper, we aim to fill this gap by introducing a hybrid drone acoustic dataset composed of recorded drone audio clips and artificially generated drone audio samples using a state-of-the-art deep learning technique known as the Generative Adversarial Network. Furthermore, we examine the effectiveness of using drone audio with different deep learning algorithms, namely, the Convolutional Neural Network, the Recurrent Neural Network and the Convolutional Recurrent Neural Network in drone detection and identification. Moreover, we investigate the impact of our proposed hybrid dataset in drone detection. Our findings prove the advantage of using deep learning techniques for drone detection and identification while confirming our hypothesis on the benefits of using the Generative Adversarial Networks to generate real-like drone audio clips with an aim of enhancing the detection of new and unfamiliar drones.
Collections
- Computer Science & Engineering [2280 items ]
Related items
Showing items related by title, author, creator and subject.
-
Fast, Reliable, and Secure Drone Communication: A Comprehensive Survey
Hassija, Vikas; Chamola, Vinay; Agrawal, Adhar; Goyal, Adit; Luong, Nguyen Cong; Niyato, Dusit; Yu, Fei Richard; Guizani, Mohsen... more authors ... less authors ( Institute of Electrical and Electronics Engineers Inc. , 2021 , Article)Drone security is currently a major topic of discussion among researchers and industrialists. Although there are multiple applications of drones, if the security challenges are not anticipated and required architectural ... -
A Distributed Approach for Networked Flying Platform Association with Small Cells in 5G+ Networks
Shah, Syed Awais W.; Khattab, Tamer; Shakir, Muhammad Zeeshan; Hasna, Mazen O. ( Institute of Electrical and Electronics Engineers Inc. , 2017 , Conference Paper)The densification of small cell base stations in a 5G architecture is a promising approach to enhance the coverage area and facilitate the ever increasing capacity demand of end users. However, the bottleneck is an intelligent ... -
Drone-SCNet: Scaled Cascade Network for Crowd Counting on Drone Images
Elharrouss O.; Almaadeed N.; Abualsaud K.; Al-Ali A.; Mohamed A.; Khattab T.; Al-Maadeed, Somaya... more authors ... less authors ( Institute of Electrical and Electronics Engineers Inc. , 2021 , Article)Crowd management is an essential task to ensure the safety and smoothness of any event. Using novel technologies, including surveillance cameras, drones, and the communication techniques between security agents, the control ...