Real-Time UAV Recognition Through Advanced Machine Learning for Enhanced Military Surveillance

Muhyeeddin Alqaraleh, Mowafaq Salem Alzboon and Mohammad Subhi Al-Batah

Gamification and Augmented Reality, 2025, vol. 3, 63

Abstract: In an era where the military utilization of Unmanned Aerial Vehicles (UAVs) has become essential for surveillance and operational operations, our study tackles the growing demand for real-time, accurate UAV recognition. The rise of UAVs presents numerous safety hazards, requiring systems that distinguish UAVs from non-threatening phenomena, such as birds. This research study conducts a comparative examination of advanced machine learning models, aiming to address the challenge of real-time aerial classification in diverse environmental conditions without model retraining. This research employs extensive datasets to train and validate models such as Neural Networks, Support Vector Machines, ensemble methods, and Gradient Boosting Machines. The fashions are evaluated based on accuracy, forgetfulness, and processing efficiency—criteria determining the viability of real-time operational scenarios. The findings indicate that Neural Networks exhibit enhanced performance, demonstrating exceptional accuracy in distinguishing UAVs from birds. This culminates in our primary assertion: Neural Networks possess vital operational security ramifications and can markedly enhance the allocation of defense resources. The findings significantly improve surveillance systems, highlighting the effectiveness of machine-learning methods in real-time UAV identification. Moreover, incorporating Neural Network systems into military defenses is recommended to enhance decision-making capabilities and security operations. Foresee forthcoming UAV developments and advocate for regular model updates to keep up with increasingly nimble and perhaps stealthier drone designs.

Date: 2025
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:dbk:gammif:v:3:y:2025:i::p:63:id:63

DOI: 10.56294/gr202563

Access Statistics for this article

More articles in Gamification and Augmented Reality from AG Editor
Bibliographic data for series maintained by Javier Gonzalez-Argote ().