A C4 Software for Anti Drone System

Mini unmanned aerial vehicles (UAVs), commonly known as small drones, have seen outstanding advancements in recent years and have been used in a variety of fields. However, their potential misuse for illegal activities and the risks they pose to safety and privacy have raised concerns. To address these issues, we propose a Command, Control, Communications, and Computers (C4) software able to manage and control anti-drone systems. Our software solution includes an easy-to-use dashboard that processes and displays video data from surveillance sensors. It incorporates AI-powered functionalities, including object detection, target tracking, and classification of small drones. At the inference stage, the network models for drone detection and classification functionalities have achieved an accuracy exceeding 96 %. We have evaluated the effectiveness of our solution by deploying it in a no-fly zone, where it successfully identified and tracked drones in near real-time. The proposed control system provides unified information with which the entire anti-drone process can be managed starting from the detection of each threat.

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Publication Details

Journal
Defence Science Journal
Published
2024-08-29
DOI
https://doi.org/10.14429/dsj.74.19504
Citations
5
Primary Topic
Metaheuristic Optimization Algorithms Research
Type
article
Field-Weighted Citation Impact
1.74
Controls
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article

A C4 Software for Anti Drone System

Feten Slimeni, Tijeni Delleji, Mohsen Lefi
5 citations
Defence Science Journal
Metaheuristic Optimization Algorithms Research
1.74
article

A C4 Software for Anti Drone System

Feten Slimeni, Tijeni Delleji, Mohsen Lefi
article en
5 citations

Abstract

Mini unmanned aerial vehicles (UAVs), commonly known as small drones, have seen outstanding advancements in recent years and have been used in a variety of fields. However, their potential misuse for illegal activities and the risks they pose to safety and privacy have raised concerns. To address these issues, we propose a Command, Control, Communications, and Computers (C4) software able to manage and control anti-drone systems. Our software solution includes an easy-to-use dashboard that processes and displays video data from surveillance sensors. It incorporates AI-powered functionalities, including object detection, target tracking, and classification of small drones. At the inference stage, the network models for drone detection and classification functionalities have achieved an accuracy exceeding 96 %. We have evaluated the effectiveness of our solution by deploying it in a no-fly zone, where it successfully identified and tracked drones in near real-time. The proposed control system provides unified information with which the entire anti-drone process can be managed starting from the detection of each threat.

Defence Science JournalVol. 74(5)
Military Hospital of Tunis (TN)
Openalex Percentile: Top 13%
Metaheuristic Optimization Algorithms Research
1.74
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