Visible to the public Drone Detection and Identification System Using Artificial Intelligence

TitleDrone Detection and Identification System Using Artificial Intelligence
Publication TypeConference Paper
Year of Publication2018
AuthorsLee, D. ', La, W. Gyu, Kim, H.
Conference Name2018 International Conference on Information and Communication Technology Convergence (ICTC)
Keywordsapproaching drone, artificial intelligence, artificial intelligence security, autonomous aerial vehicles, camera images, Cameras, classifier, composability, comprehensive drone detection system, control engineering computing, Deep Learning, detection, Detectors, drone identification system, drone imagery, drone industry, drones, feature extraction, Human Behavior, image processing, learning (artificial intelligence), machine learning, Metrics, object detection, OpenCV library, pubcrawl, Resiliency, robot vision, surveillance
Abstract

As drone attracts much interest, the drone industry has opened their market to ordinary people, making drones to be used in daily lives. However, as it got easier for drone to be used by more people, safety and security issues have raised as accidents are much more likely to happen: colliding into people by losing control or invading secured properties. For safety purposes, it is essential for observers and drone to be aware of an approaching drone. In this paper, we introduce a comprehensive drone detection system based on machine learning. This system is designed to be operable on drones with camera. Based on the camera images, the system deduces location on image and vendor model of drone based on machine classification. The system is actually built with OpenCV library. We collected drone imagery and information for learning process. The system's output shows about 89 percent accuracy.

URLhttps://ieeexplore.ieee.org/document/8539442
DOI10.1109/ICTC.2018.8539442
Citation Keylee_drone_2018