Drones have garnered great popularity due to their widespread applications across various industries, ranging from surveillance and reconnaissance to logistics and entertainment. However, the increasing use of drones has also given platform to potential security threat activities, such as unauthorized surveillance, smuggling, and privacy invasion. As a result, there is need to develop efficient and reliable drone detection systems to safeguard sensitive areas and public spaces. This paper focuses on the development and implementation of an inclusive drone detection system based on advanced signal processing techniques and machine learning algorithms and deep learning algorithms. The proposed system aims to identify and classify drones with highest accuracy on real world datasets. Using the real-world datasets and different highly accurate techniques for classification the model developed is reliable and can be directly used for advance practical purposes.
Article Details
Unique Paper ID: 161392
Publication Volume & Issue: Volume 10, Issue 3
Page(s): 504 - 512
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