AUTOMATIC DRONE DETECTION SYSTEM

AUTOMATIC DRONE DETECTION SYSTEM

Vishnuvardhini P, IV year CST, SNS College of Engineering, Coimbatore. Email : vishnuvardhini19@gmail.com

Praveen kumar S, IV year CST, SNS College of Engineering, Coimbatore. Email : praveenkumar165516@gmail.com

Udhayakumar P, IV year CST, SNS College of Engineering, Coimbatore. Email : udhayaakumar347@gmail.com

Pradeep R, IV year CST, SNS College of Engineering, Coimbatore. Email : rpradeep1862@gmail.com

Saraswathi R, Assistant Professor, SNS College of Engineering, Email: sarasrajagopal2@gmail.com

Abstract

The Automatic Drone Detection System (ADDS) is designed to address the growing concern of unauthorized drone operations in restricted or sensitive airspaces. With the rapid proliferation of unmanned aerial vehicles (UAVs), there is a need for an effective solution to detect, track, and mitigate potential threats posed by drones. This system utilizes a combination of advanced technologies such as radar, machine learning algorithms, and computer vision to identify and classify drones in real-time. The system employs passive and active sensors, including radar and cameras, to monitor a specified airspace for UAV activity. By analyzing the captured data, the system can detect drones' flight patterns, predict their trajectory, and distinguish them from other airborne objects. The use of machine learning models enhances the system's accuracy in drone detection, reducing false positives and improving overall reliability. The ADDS aims to provide a comprehensive, automated solution for security and airspace management, with applications in airports, military installations, critical infrastructure, and public safety.