The Role of Artificial Intelligence Supported Unmanned Aerial Vehicles in Disaster Management

Bülent Yıldız

Makale detayları

The Role of Artificial Intelligence Supported Unmanned Aerial Vehicles in Disaster Management

Yazarlar:

Bülent Yıldız

Yayıncı:

Mustafa Süleyman ÖZCAN

Ana Başlıklar:

Karşılaştırmalı Ekonomik Sistemler | Sürdürülebilir Kalkınma

Dergi:

İnsan ve Toplum Bilimleri Araştırmaları Dergisi Vol.14 Issue 3, pp.2012-2032

Belge Tipi:

Makale

Yayın Tarihi:

9/2025

Belge Dili:

Türkçe

Document ID (Org No.):

2001358057

pISSN:

2147-1185

Anahtar kelimeler:

Özet:

 Disasters are events caused by the uncontrolled occurrence of natural phenomena or man-made hazards, leading to large-scale loss of life, property and environment. Disasters such as earthquakes, floods, forest fires, technological accidents and nuclear leaks create situations that require immediate intervention and have long-term social and economic impacts. Factors such as increasing urbanisation, climate change, population density and environmental degradation increase both the frequency and severity of these disasters. Therefore, it is no longer sufficient to carry out disaster management based only on traditional methods; integration of new generation technological solutions becomes inevitable. This study aims to examine the contributions of artificial intelligence AI-supported unmanned aerial vehicles UAVs in disaster management processes and to evaluate the possibilities of using these technologies according to different types of disasters from a multidimensional perspective. In the study, qualitative method based on literature review was used and national and international sources were analysed comparatively. The roles of AI-supported UAVs in disaster preparedness, response and recovery phases are discussed through operational advantages, limitations and application examples. The findings reveal that these technologies offer fast and effective solutions in tasks such as search and rescue, damage assessment, material delivery, access to hazardous areas, real-time data collection and communication, especially in critical time periods such as the first 72 hours of the disaster. Real-time imaging, damage assessment, search and rescue support, access to hazardous areas, material transport, establishment of communication networks and mapping of risky areas have been determined to make significant contributions. Moreover, AI is integrated with big data analytics, machine learning, deep learning and remote sensing systems into critical decision support processes such as disaster forecasting, development of early warning systems and prioritisation of resources. The combined use of these technologies represents not only a technical convenience but also a strategic paradigm shift in disaster management. The study draws attention to the need for a multi-stakeholder transformation in the areas of policy, education, legislation and technical capacity by developing concrete recommendations for decision makers.

 Disasters are events caused by the uncontrolled occurrence of natural phenomena or man-made hazards, leading to large-scale loss of life, property and environment. Disasters such as earthquakes, floods, forest fires, technological accidents and nuclear leaks create situations that require immediate intervention and have long-term social and economic impacts. Factors such as increasing urbanisation, climate change, population density and environmental degradation increase both the frequency and severity of these disasters. Therefore, it is no longer sufficient to carry out disaster management based only on traditional methods; integration of new generation technological solutions becomes inevitable. This study aims to examine the contributions of artificial intelligence AI-supported unmanned aerial vehicles UAVs in disaster management processes and to evaluate the possibilities of using these technologies according to different types of disasters from a multidimensional perspective. In the study, qualitative method based on literature review was used and national and international sources were analysed comparatively. The roles of AI-supported UAVs in disaster preparedness, response and recovery phases are discussed through operational advantages, limitations and application examples. The findings reveal that these technologies offer fast and effective solutions in tasks such as search and rescue, damage assessment, material delivery, access to hazardous areas, real-time data collection and communication, especially in critical time periods such as the first 72 hours of the disaster. Real-time imaging, damage assessment, search and rescue support, access to hazardous areas, material transport, establishment of communication networks and mapping of risky areas have been determined to make significant contributions. Moreover, AI is integrated with big data analytics, machine learning, deep learning and remote sensing systems into critical decision support processes such as disaster forecasting, development of early warning systems and prioritisation of resources. The combined use of these technologies represents not only a technical convenience but also a strategic paradigm shift in disaster management. The study draws attention to the need for a multi-stakeholder transformation in the areas of policy, education, legislation and technical capacity by developing concrete recommendations for decision makers.

 Disasters are events caused by the uncontrolled occurrence of natural phenomena or man-made hazards, leading to large-scale loss of life, property and environment. Disasters such as earthquakes, floods, forest fires, technological accidents and nuclear leaks create situations that require immediate intervention and have long-term social and economic impacts. Factors such as increasing urbanisation, climate change, population density and environmental degradation increase both the frequency and severity of these disasters. Therefore, it is no longer sufficient to carry out disaster management based only on traditional methods; integration of new generation technological solutions becomes inevitable. This study aims to examine the contributions of artificial intelligence AI-supported unmanned aerial vehicles UAVs in disaster management processes and to evaluate the possibilities of using these technologies according to different types of disasters from a multidimensional perspective. In the study, qualitative method based on literature review was used and national and international sources were analysed comparatively. The roles of AI-supported UAVs in disaster preparedness, response and recovery phases are discussed through operational advantages, limitations and application examples. The findings reveal that these technologies offer fast and effective solutions in tasks such as search and rescue, damage assessment, material delivery, access to hazardous areas, real-time data collection and communication, especially in critical time periods such as the first 72 hours of the disaster. Real-time imaging, damage assessment, search and rescue support, access to hazardous areas, material transport, establishment of communication networks and mapping of risky areas have been determined to make significant contributions. Moreover, AI is integrated with big data analytics, machine learning, deep learning and remote sensing systems into critical decision support processes such as disaster forecasting, development of early warning systems and prioritisation of resources. The combined use of these technologies represents not only a technical convenience but also a strategic paradigm shift in disaster management. The study draws attention to the need for a multi-stakeholder transformation in the areas of policy, education, legislation and technical capacity by developing concrete recommendations for decision makers.

 Afetler, doğa olaylarının veya insan kaynaklı tehlikelerin kontrolsüz biçimde ortaya çıkmasıyla oluşan, geniş çaplı can, mal ve çevre kayıplarına yol açan olaylardır. Depremler, seller, orman yangınları, teknolojik kazalar ve nükleer sızıntılar gibi afetler, hem ani müdahale gerektiren durumlar yaratmakta hem de uzun vadeli sosyal ve ekonomik etkiler doğurmaktadır. Artan kentleşme, iklim değişikliği, nüfus yoğunluğu ve çevresel bozulma gibi etkenler, bu afetlerin hem sıklığını hem de şiddetini artırmaktadır. Bu nedenle, afet yönetiminin yalnızca geleneksel yöntemlere dayalı olarak yürütülmesi artık yeterli olmamakta; yeni nesil teknolojik çözümlerin entegrasyonu kaçınılmaz hâle gelmektedir. Bu çalışma, afet yönetimi süreçlerinde yapay zekâ YZ destekli insansız hava araçlarının İHA sunduğu katkıları incelemeyi ve bu teknolojilerin farklı afet türlerine göre kullanım olanaklarını çok boyutlu bir perspektifle değerlendirmeyi amaçlamaktadır. Çalışmada literatür taramasına dayalı nitel yöntem kullanılmış, ulusal ve uluslararası kaynaklar karşılaştırmalı olarak analiz edilmiştir. YZ destekli İHAların afetin hazırlık, müdahale ve iyileştirme aşamalarında üstlendiği roller; operasyonel avantajlar, sınırlılıklar ve uygulama örnekleri üzerinden ele alınmıştır. Elde edilen bulgular, bu teknolojilerin özellikle afetin ilk 72 saati gibi kritik zaman diliminde arama-kurtarma, hasar tespiti, malzeme ulaştırma, tehlikeli bölgelere erişim sağlama, gerçek zamanlı veri toplama ve iletişim kurma gibi görevlerde hızlı ve etkili çözümler sunduğunu ortaya koymaktadır. Gerçek zamanlı görüntüleme, hasar tespiti, arama-kurtarma desteği, tehlikeli alanlara erişim, malzeme ulaştırma, iletişim ağlarının kurulması ve riskli bölgelerin haritalanması gibi görevlerde önemli katkılar sunduğu belirlenmiştir. Ayrıca YZ; büyük veri analitiği, makine öğrenmesi, derin öğrenme ve uzaktan algılama sistemleriyle afet tahmini, erken uyarı sistemlerinin geliştirilmesi ve kaynakların önceliklendirilmesi gibi kritik karar destek süreçlerine entegre olmaktadır. Bu teknolojilerin birlikte kullanımı, afet yönetiminde yalnızca teknik bir kolaylık değil, aynı zamanda stratejik bir paradigma değişimini temsil etmektedir. Çalışma, karar vericilere yönelik somut öneriler geliştirerek politika, eğitim, mevzuat ve teknik kapasite alanlarında çok paydaşlı bir dönüşüm ihtiyacına dikkat çekmektedir.

Makale detayları

The Role of Artificial Intelligence Supported Unmanned Aerial Vehicles in Disaster Management

Yazarlar:

Bülent Yıldız

Yayıncı:

Mustafa Süleyman ÖZCAN

Ana Başlıklar:

Karşılaştırmalı Ekonomik Sistemler | Sürdürülebilir Kalkınma

Dergi:

İnsan ve Toplum Bilimleri Araştırmaları Dergisi Vol.14 Issue 3, pp.2012-2032

Belge Tipi:

Makale

Yayın Tarihi:

9/2025

Belge Dili:

Türkçe

Document ID (Org No.):

2001358057

pISSN:

2147-1185

Disaster Management

Artificial İntelligence

Unmanned Aerial Vehicles

Early Warning Systems

Big Data

Response Strategies.Afet Yönetimi

Yapay Zekâ

İnsansız Hava Araçları

Erken Uyarı Sistemleri

Büyük Veri

Müdahale Stratejileri

Sayı

Makale detayları

Yazarlar: Bülent Yıldız

Yayıncı: Mustafa Süleyman ÖZCAN

Ana Başlıklar: Karşılaştırmalı Ekonomik Sistemler | Sürdürülebilir Kalkınma

Dergi: İnsan ve Toplum Bilimleri Araştırmaları Dergisi Vol.14 Issue 3, pp.2012-2032

Belge Tipi: Makale

Yayın Tarihi: 9/2025

Belge Dili: Türkçe

Document ID (Org No.): 2001358057

pISSN: 2147-1185

Sayı

Yazarlar:

Bülent Yıldız

Yayıncı:

Mustafa Süleyman ÖZCAN

Ana Başlıklar:

Karşılaştırmalı Ekonomik Sistemler | Sürdürülebilir Kalkınma

Dergi:

İnsan ve Toplum Bilimleri Araştırmaları Dergisi Vol.14 Issue 3, pp.2012-2032

Belge Tipi:

Makale

Yayın Tarihi:

9/2025

Belge Dili:

Türkçe

Document ID (Org No.):

2001358057

pISSN:

2147-1185