Authors : Malay Karmakar

Volume/Issue : Volume 10 - 2025, Issue 12 - December

Google Scholar : https://tinyurl.com/kt3hd5rh

Scribd : https://tinyurl.com/4vesk7t4

DOI : https://doi.org/10.38124/ijisrt/25dec1402

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Drones have increasingly been exploited by adversaries in border regions to transport contraband such as drugs and weapons. The widespread adoption of drone technology across various sectors has brought significant advantages, but also raised critical concerns involving security, privacy, and regulatory oversight. With the growing density of drones operating in shared airspace, it becomes essential to develop reliable systems for drone recognition and classification to promote safe airspace management. This paper presents a novel technique that integrates computer vision and machine learning to identify and categorize drones effectively. Utilizing advanced deep learning models, our approach extracts distinctive features from images of drones captured by surveillance systems or sensors. These features are then classified into specific drone categories using the YOLOv8 algorithm, enabling real-time detection and monitoring. We validate our method on a diverse dataset comprising multiple drone types and varying environmental scenarios. The experimental findings reveal robust performance and scalability, with high accuracy for both identification and classification tasks. Additionally, we explore the relevance of our system in critical applications such as law enforcement, border patrol, infrastructure surveillance, and emergency management. This work advances drone detection methodologies and addresses key challenges in integrating drones safely within civilian airspace.

Keywords : DPM, RCNN, SSD, PAN FPN, YOLO-V8, ERB, FFNB, YOLOMG.

References :

1. Valentak Z (2018) Drone market share analysis. http://www.dronesglobe.com/news/drone-market-share-analysis-predictions-2018/.
2. Jansen B (2015) Drone crash at white house reveals security risks. USA Today.
3. Jouan A (2014) Survols de centrales: un expert reconnu s’ inquiète. http://www.lefigaro.fr/actualite-france/2014/11/25/01016-20141125ARTFIG00024-survols-de-centrales-un-expert-reconnu-s-inquiete.php.
4. Serna J (2016) Lufthansa jet and drone nearly collide near lax. LA Times.
5. Gallagher S (2013) German chancellor’s drone ‘attack’ shows the threat of weaponized uavs. Ars Technica.
6. Dinan S (2017) Drones become latest tool drug cartels use to smuggle drugs into u.s. https://www.washingtontimes.com/news/2017/aug/20/mexican-drug-cartels-using-drones-to-smuggle-heroi/.
7. Zhang L, Young S (2018) China busts smugglers using drones to transport smartphones: state media. https://www.reuters.com/article/us-china-crime-smartphones-smugglers/china-busts-smugglers-using-drones-to-transport-smartphones-state-media-idUSKBN1H60BT.
8. BBC (2018) Charges over drone drug smuggling into prisons. https://www.bbc.com/news/uk-england-43413134.
9. Mr. Shaikh Asif Basha, Dr.D Jagadeeshan,Mr V.Maruthi Prasad Drone Detection and classification using Machine Learning Vol.9 Issue.6 June 2022.
10. Drozdowicz J, Wielgo M, Samczynski P, Kulpa K, Krzonkalla J, Mordzonek M, Bryl M, Jakielaszek Z (2016) 35 ghz fmcw drone detection system In: Radar Symposium (IRS), 2016 17th International, 1–4.. IEEE.
11. Redmon J, Divvala S, Girshick R, Farhadi A (2016) You only look once: Unified, real-time object detection In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 779–788.
12. (2018) Introduction to Dedrones Airspace Security Platform. https://www.dedrone.com/webinars/introduction-to-dedrones-airspace-security-platform-11-28-2018. Accessed: 22 Oct 2018.
13. Mendis GJ, Randeny T, Wei J, Madanayake A (2016) Deep learning based doppler radar for micro uas detection and classification In: Military Communications Conference, MILCOM 2016-2016 IEEE, 924–929.. IEEE.
14. Ganti SR, Kim Y (2016) Implementation of detection and tracking mechanism for small uas In: Unmanned Aircraft Systems (ICUAS), 2016 International Conference On, 1254–1260.. IEEE.
15. Kwag Y-K, Woo I-S, Kwak H-Y, Jung Y-H (2016) Multi-mode sdr radar platform for small air-vehicle drone detection In: Radar (RADAR), 2016 CIE International Conference On, 1–4.. IEEE.
16. Laurenzis M, Hengy S, Hommes A, Kloeppel F, Shoykhetbrod A, Geibig T, Johannes W, Naz P, Christnacher F (2017) Multi-sensor field trials for detection and tracking of multiple small unmanned aerial vehicles flying at low altitude In: Signal Processing, Sensor/Information Fusion, and Target Recognition XXVI, vol. 10200, 102001.. International Society for Optics and Photonics.
17. Kim BH, Khan D, Bohak C, Kim JK, Choi W, Lee HJ, Kim MY (2018) Ladar data generation fused with virtual targets and visualization for small drone detection system In: Technologies for Optical Countermeasures XV, vol. 10797, 107970.. International Society for Optics and Photonics.
18. Hauzenberger L, Holmberg Ohlsson E (2015) Drone detection using audio analysis.
19. Nam SY, Joshi GP (2017) Unmanned aerial vehicle localization using distributed sensors. Int J Distrib Sensor Networks 13(9):1550147717732920. Article Google Scholar
20. LeCun Y, Bengio Y, Hinton G (2015) Deep learning. Nature 521(7553):436. Article Google Scholar
21. Taigman Y, Yang M, Ranzato M, Wolf L (2014) Deepface: Closing the gap to human-level performance in face verification In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 1701–1708.
22. Schumann A, Sommer L, Klatte J, Schuchert T, Beyerer J (2017) Deep cross-domain flying object classification for robust uav detection In: Advanced Video and Signal Based Surveillance (AVSS), 2017 14th IEEE International Conference On, 1–6.. IEEE.
23. Aker C, Kalkan S (2017) Using deep networks for drone detection. arXiv preprint arXiv:1706.05726.
24. Saqib M, Khan SD, Sharma N, Blumenstein M (2017) A study on detecting drones using deep convolutional neural networks In: 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), 1–5.. IEEE.
25. (2018) How Droneshield works?. https://www.droneshield.com/how-droneshield-works/. Accessed: 22 Oct 2018.
26. (2018) Gryphon Skylight System. Detect, track and classify moving objects in your airspace. https://www.srcinc.com/pdf/Radars-and-Sensors-Gryphon-Skylight.pdf. Accessed: 22 Oct 2018.
27. Fan H, Zheng L, Yan C, Yang Y (2018) Unsupervised person re-identification: Clustering and fine- tuning. ACM Trans Multimed Comput Commun Appl (TOMM) 14(4):83.