Drone Detection and Surveillance

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.