Drone Detection and Surveillance

Author(s)	K S Bhavishya, Kodatala Yaswanth Reddy, Gudikal Sai Vamsi, Isukapalli Sai Krishnachaithanya
Country	India
Abstract	This paper presents a deep learning-based solution for detecting and identifying drones to address security concerns. By leveraging A9G-based GPS tracker modules, the system achieves real-time tracking and differentiation between authorized and unauthorized drones. The proposed model demonstrates high performance with an F-1 score of 93.63%, precision of 96.2%, mAp of 95%, recall of 91.2%, and accuracy of 95.5%. Authorized drone locations can be communicated via SMS for prompt action if an unauthorized drone is detected.
Keywords	YOLOv5, A9G-based GPS tracker, XIAO ESP32C3 board
Field	Engineering
Published In	Volume 5, Issue 3, May-June 2023
Published On	2023-05-31
Cite This	Drone Detection and Surveillance - K S Bhavishya, Kodatala Yaswanth Reddy, Gudikal Sai Vamsi, Isukapalli Sai Krishnachaithanya - IJFMR Volume 5, Issue 3, May-June 2023. DOI 10.36948/ijfmr.2023.v05i03.3357
DOI	https://doi.org/10.36948/ijfmr.2023.v05i03.3357
Short DOI	https://doi.org/gr97sp

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