Detection of Drone Using CCTV Live Feed

Abstract

Drones are intended to create innovation and economic opportunities, but they also offer security risks. We provide technology that detects drones in real time using CCTV feeds, which is incredibly important in protecting our establishments and sensitive locations. Our solution is intelligent enough to recognize birds, and other flying objects from drones and detect them from afar. The YOLO algorithm will provide an optimal solution in real-time, our application alerts authorities when drones are spotted closer. A single convolutional neural network is used by the YOLO algorithm, a real-time object-detection system, to identify objects in a picture. The algorithm is evaluated on a set of test images after being trained on a collection of drone images to see how well it performs. Results show that the YOLO algorithm can accurately detect drones in images with a high detection rate and low false positive rate. This method can be used for various applications such as security surveillance and airspace management. Overall, this demonstrates the effectiveness of using the YOLO algorithm for drone detection in real-world scenarios.