DRONE DETECTION THROUGH LIVE CAMERA USING YOLOv3

DRONE DETECTION THROUGH LIVE CAMERA USING YOLOv3

¹Ms. E. Padma, ²Mr. A.S.H. PRANAV, ³Mr. C. Adithya Siddhartha

¹Assistant Professor,²Graduate Student,³ Graduate student

Dept. of Computer Science Engineering,

SCSVMV (Deemed to be University), Enathur, India

Abstract: The production of unmanned aerial vehicle (UAV) also known as drones is increasing day by day and they are easily accessible to almost everyone. There are many uses of drones in the real world like medical industry also in defense. But the increase in drones also increased the safety concerns. This is because they are being used to perform terror attacks causing serious threats to public. Hence it has become very essential to detect and neutralize these drones in the real world. There are radar systems which detect these drones but we need more than that to detect these drones accurately. Radar can detect drones with a larger RCS at a greater distance that a drone with a small RCS. Typically, radar systems can detect drones up to 1 mile away for a Phantom 4 Size drone. The range is affected by Drone size. Radar detection range is also slightly affected by weather conditions like rain and fog. Computer vision is such technology with which we can detect the drones with a decent accuracy. Our project is to detect drones through a live camera at any atmosphere. We used some popular frameworks and machine learning algorithms with computer vision to make this project work.

Keywords: Machine Learning, Deep Learning, Python, YOLOv3.