DESIGN OF A SECURITY CONCEPT UTILIZING BVLOS FLIGHTS AND YOLO-BASED OBJECT DETECTION

Recent shifts in Europe's security landscape driven by evolving hybrid warfare tactics require innovative solutions for real-time threat detection. This paper presents a security concept leveraging Beyond Visual Line Of Sight (BVLOS) drone flights combined with state-of-the-art YOLO-based object detection to enhance surveillance capabilities. By integrating advanced drone technology with AI-driven video analysis, the proposed system aims to detect armed individuals and mitigate potential hybrid attacks in critical infrastructure areas. A specialized dataset is prepared to improve detection accuracy and response times, ensuring cost-effective, autonomous monitoring in high-risk scenarios. This approach offers a robust solution for proactive perimeter security, optimizing resource allocation and reinforcing safety measures in an increasingly volatile environment. The results indicate substantial promise for future security implementations.

Authors

Publication Details

Journal
MM Science Journal
Published
2025-05-25
DOI
https://doi.org/10.17973/mmsj.2025_06_2025022
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
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article

DESIGN OF A SECURITY CONCEPT UTILIZING BVLOS FLIGHTS AND YOLO-BASED OBJECT DETECTION

L. Hřič, Daniela Perduková, Ján Bačík
MM Science Journal
Robotic Path Planning Algorithms
article

DESIGN OF A SECURITY CONCEPT UTILIZING BVLOS FLIGHTS AND YOLO-BASED OBJECT DETECTION

L. Hřič, Daniela Perduková, Ján Bačík
article en

Abstract

Recent shifts in Europe's security landscape driven by evolving hybrid warfare tactics require innovative solutions for real-time threat detection. This paper presents a security concept leveraging Beyond Visual Line Of Sight (BVLOS) drone flights combined with state-of-the-art YOLO-based object detection to enhance surveillance capabilities. By integrating advanced drone technology with AI-driven video analysis, the proposed system aims to detect armed individuals and mitigate potential hybrid attacks in critical infrastructure areas. A specialized dataset is prepared to improve detection accuracy and response times, ensuring cost-effective, autonomous monitoring in high-risk scenarios. This approach offers a robust solution for proactive perimeter security, optimizing resource allocation and reinforcing safety measures in an increasingly volatile environment. The results indicate substantial promise for future security implementations.

MM Science JournalVol. 2025(2)
Openalex Percentile: Top 90%
Robotic Path Planning Algorithms
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