Geniş Alan Gözetimi ve Güvenliği için Görüntü İşleme Tabanlı Otonom İHA Sisteminin Tasarımı ve Gerçekleştirilmesi

Öz

Bu çalışma, belirli alanların izinsiz girişlerden korunmasını sağlamak amacıyla geliştirilen otonom bir drone sisteminin tasarımını ve gerçeklenmesini sunmaktadır. Raspberry Pi ve kamera ile donatılan drone, belirli bir yükseklikten çevreyi sürekli olarak taramakta, elde edilen görsel verileri işleyerek izlenen bölgedeki hareketleri otonom şekilde tespit etmektedir. Donanım ve yazılım bileşenlerinden oluşan İHA üzerine entegre edilen sensörler, kullanılan görüntü işleme algoritmaları ve çevrimiçi veri kümeleri ile eğitilen derin öğrenme tabanlı model sayesinde güvenlik ihlalleri gerçek zamanlı olarak algılanabilmektedir. İhlal tespiti durumunda, sistem sesli bir uyarı mekanizması devreye sokmakta ve tehdit unsuru alandan uzaklaşana kadar takipte kalmaktadır. Geleneksel güvenlik sistemlerinden farklı olarak, fiziksel altyapıya gerek kalmaksızın havadan izleme-değerlendirme yapabilmesi ve caydırıcılığı artıran bir uyarı sistemine sahip olması projeye özgünlük kazandırmaktadır. Ayrıca, tasarlanan drone, hafif yapısı ve esnek kullanım kabiliyeti sayesinde farklı coğrafi koşullarda güvenilir biçimde çalışabilmektedir. İHA’nın dış mekan uçuş testleri gerçekleştirilmiş, elde edilen veriler değerlendirilmiş ve sistemin yaklaşık %92 oranında kişi algılama doğruluğuna ve yaklaşık 0,97 kesinlik değerine ulaştığı, ortalama 2,6 FPS hızında gerçek zamanlı çalışabildiği gösterilmiştir. Elde edilen sonuçlar, geliştirilen sistemin geleneksel güvenlik sistemlerine kıyasla maliyet etkin bir alternatif olarak yüksek doğruluk, kararlılık ve caydırıcılık özellikleri ile öne çıktığını göstermektedir.

Anahtar Kelimeler

• Otonom drone
• görüntü işleme
• güvenlik sistemi
• gerçek zamanlı tespit
• maliyet etkin

Destekleyen Kurum

Bu çalışma herhangi bir dış finansman almamıştır.

Etik Beyan

Çalışmada etik uygunluk bildirisi gerekmemektedir.

Design and Realization of an Image Processing–Based Autonomous UAV System for Large-Area Surveillance and Security

Öz

This study presents the design and implementation of an autonomous drone system developed to ensure the protection of specific areas against unauthorized intrusions. Equipped with a Raspberry Pi and a camera, the drone continuously scans the environment from a certain altitude and autonomously detects movements in the monitored area by processing the obtained visual data. The UAV, consisting of hardware and software components, is capable of detecting security violations in real time through integrated sensors, applied image processing algorithms, and a deep learning–based model trained with online datasets. In the event of an intrusion, the system activates an audible warning mechanism and continues tracking until the threat is removed from the area. Unlike traditional security systems, the ability to perform aerial monitoring and evaluation without the need for physical infrastructure and the presence of a deterrence-enhancing warning system provide originality to the project. In addition, the designed drone can operate reliably under different geographical conditions due to its lightweight structure and flexible usage capability. Outdoor flight tests of the UAV were conducted, the obtained data were evaluated, and it was shown that the system achieved approximately %92 person detection accuracy and a precision value of about 0.97, while operating in real time at an average speed of 2.6 FPS. The obtained results indicate that the developed system stands out as a cost-effective alternative to traditional security systems in terms of high accuracy, stability, and deterrence.

Anahtar Kelimeler

• Autonomous drone
• image processing
• security system
• real-time detection
• cost-effective

Destekleyen Kurum

Bu çalışma herhangi bir dış finansman almamıştır.

Etik Beyan

Çalışmada etik uygunluk bildirisi gerekmemektedir.

Kaynakça

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