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Evaluation of The Studies on Unmanned Aircraft System Safety Management Systems with Bibliometric Analysis

Yıl 2024, Cilt: 6 Sayı: 2, 132 - 148, 29.08.2024
https://doi.org/10.51785/jar.1453011

Öz

UAV operations and their literature are developing rapidly. Along with the increasing number of risky situations, new technologies and measures are being developed to eliminate the unsafe situations created by them. Increasing UAVs have potential to lead to unsafe situations in airspace with incident and accident background. In addition to all other studies related to UAVs, studies on safety management systems, as well as other topics related to the safety management system, need to increase. In this study, a bibliometric analysis of the studies on UAVs between the years 2003-2022 was conducted from the perspective of safety management. For this purpose, the publications found in the Dimensions database were examined. Those publications related to UAVs were filtered according to certain criteria such as year, author, country, institution, and a sample was formed with 741 publications by using bibliometric analysis method. VOSViewer application was used for bibliometric analysis and the achieved data were visualized in the form of tables, graphics and visual maps. The findings show that the vast majority of publications on keywords were published in 2021. The most cited publication was written by Colomina and Molina in 2014. Most of the publications came up from the United States of America in total where 86 studies were conducted. The most cited organization is the University of Florida. In the cluster work, the words of remote sensing, sensor, and drones appear frequently.

Kaynakça

  • Abdel-Basset, M., Chang, V., & Nabeeh, N. A. (2020). An intelligent framework using disruptive technologies for COVID-19 analysis. Technological Forecasting & Social Change, 163, 120431.
  • Alshamhi, S. H., Ma, O., Ansari, M. S., & Almalki, F. A. (2019). Survey on collaborative smart drones and internet of things for improving smartness of smart cities. IEEE Access, 7, 128125-128152.
  • Alvarado, E. (2023, November 5). Survey Snapshot: Spain's Drone Market. Retrieved from Drone Industry Insights: https://droneii.com/drone-companies-in-spain-drone-market
  • Altıntaş, O.A. (2023). Analysis of unmanned aerial vehicle systems occurrence reports from the safety management system perspective and scope of ICAO standards. Eskişehir Teknik Üniversitesi, Lisansüstü Eğitim Enstitüsü, Eskişehir. https://tez.yok.gov.tr/UlusalTezMerkezi/TezGosterkey=a0OMTmEd_3mfOBxT8SiBTIzaePYMbQEyFvTJuotgqKLBLfuI6rsN9LAdO9xMElRw.
  • Balasingam, M. (2017). Drones in medicine - the rise of machines. International Journal of Clinical Practice, 71(9), e12989.
  • Blyenburgh, P. v. (2021). RPAS The Global Perspective Volume 1. Retrieved from Remotely Piloted Systems The International Information & Reference Source: https://rps-info.com/publications/rpas-the-global-perspective_volume-1_2021_flipbook/
  • Carr, E. B. (2013). Unmanned aerial vehicles: Examining the safety, security, privacy and regulatory issues of integration into US airspace. National Centre for Policy Analysis (NCPA). Retrieved on September, 23(2013), 2014.
  • Colomina, I., & Molina, P. (2014). Unmanned aerial systems for photogrammetry and remote sensing: A review. ISPRS Journal of Photogrammetry and Remote Sensing, 92, 79-97.
  • Cruz, H., Eckert, M., Meneses, J., & Martínez, J.-F. (2016). Efficient forest fire detection index for application in unmanned aerial systems (UASs). Sensorns, 16(6), 893.
  • Ding, G., Wu, Q., Zhang, L., Lin, Y., Tsiftsis, T. A., & Yao, Y.-D. (2017). An amateur drone surveillance system based on the cognitive internet of things. IEEE Communications Magazine, 56(1), 29-35.
  • Dirik, D., Eryılmaz, İ. ve Erhan, T. (2023), Post-truth kavramı üzerine yapılan çalışmaların Vosviewer ile bibliyometrik analizi, Sosyal Mucit Academic Review, 4 (2), 164-188.
  • Dixit, A., & Jakhar, S. K. (2021). Airport capacity management: A review and bibliometric analysis. Journal of Air Transport Management, 91, 102010.
  • FAA. (2022, May 19). Safety Management System: SMS Explained. Retrieved from Federal Aviation Administration: https://www.faa.gov/about/initiatives/sms/explained
  • Forlani, G., Dall'Asta, E., Diotri, F., Cella, U. M., Roncella, R., & Santise, M. (2018). Quality assessment of DSMs produced from UAV flights georeferenced with on-board RTK positioning. Remote Sensing, 10(2), 311.
  • IATA. (2023). IATA Annual safety report executive summary and safety overview – 60th Edition. https://www.iata.org/contentassets/a8e49941e8824a058fee3f5ae0c005d9/safety-report-executive-and-safety-overview-2023.pdf
  • Naqvi, S. A.R, Hassan, S. A., Pervaiz, H., & Ni, Q. (2018). Drone-aided communication as a key enabler for 5G and resilient public safety networks. IEEE Communications Magazine, 56(1), 36-42.
  • Newman, M. E. (2004). Coauthorship networks and patterns of scientific collaboration. Proceedings of the national academy of sciences, 101(suppl_1), 5200-5205.
  • Perez, H., Tah, J. H., & Mosavi, A. (2019). Deep learning for detecting building defects using convolutional neural networks. Sensors, 19(16), 3556.
  • Pierdicca, R., Malinverni, E. S., Piccinini, F., Paolanti, M., Felicetti, A., & Zingaretti, P. (2018). Deep convolutional neural Network for automatic detection of damaged photovoltaic cells. Remote Sensing and Spatial Information Sciences, 42, 893-900.
  • Rosser, Jr, J. C., Vignesh, V., Terwilliger, B. A., & Parker, B. C. (2018). Surgical and medical applications of drones: A comprehensive review. Journal of The Society of Laparoscopis & Robotic Surgeons, 22(3).
  • Sandbrook, C. (2015). The social implications of using drones for biodiversity. Ambio, 44(Suppl 4), 636-647. Taha, B., & Shoufan, A. (2019). Machine learning-based drone detection and classification: state-of-the-art in research. IEEE Access, 7, 138669-138682.
  • Visser, M., Eck, N. J., & Waltman, L. (2021). Large-scale comparison of bibliographic data sources: Scopus, Web of Science, Dimensions, Crossref, and Microsoft Academic. Quantitative Science Studies, 2(1), 20-41.
  • Watss, A. C., Ambrosia, V. G., & Hinkley, E. A. (2012). Unmanned aircraft systems in remote sensing and scientific research: Classification and considerations of use. Remote Sensing, 4(6), 1671-1692.
  • Weibel, R. E., & Hansman, R. J. (2006). Safety considerations for operation of unmanned aerial vehicles in the national airspace system. Technical report, ICAT 2005-01.
  • Yang, H.-H., Chang, Y.-H., & Lin, C.-H. (2022). A combined approach for selecting drone management strategies based on the ICAO Safety Management System (SMS) components. Journal of Air Transport Management, 104, 102257.
  • Zeng, Z., Chen, P.-J., & Lew, A. A. (2020). From high-touch to high-tech: COVID-19 drives. Tourism Geographies, 22(3), 724-734.

İnsansız Hava Aracı Sistemlerinin Emniyet Yönetim Sistemlerine İlişkin Çalışmaların Bibliyometrik Analiz İle Değerlendirilmesi

Yıl 2024, Cilt: 6 Sayı: 2, 132 - 148, 29.08.2024
https://doi.org/10.51785/jar.1453011

Öz

İHA operasyonları ve literatürü hızla gelişiyor. Riskli durumların artmasıyla birlikte, bunların yarattığı emniyetsiz durumları ortadan kaldırmak için yeni teknolojiler ve önlemler geliştirilmektedir. Artan UAV'ler hava sahasında emniyetsiz durumlara yol açmaktadır. UAV'lerle ilgili diğer tüm çalışmaların yanı sıra emniyet yönetim sistemi ile ilgili diğer konu başlıklarının yanı sıra emniyet yönetim sistemlerine ilişkin çalışmalarında artması gerekmektedir. Bu çalışmada 2003-2022 yılları arasında İHA'lar üzerinde yapılan çalışmaların emniyet yönetimi perspektifinden bibliyometrik analizi yapılmıştır. Bu amaçla Dimensions veri tabanında bulunan yayınlar incelenmiştir. İHA'larla ilgili yayınlar yıl, yazar, ülke, kurum gibi belirli kriterlere göre filtrelenmiş ve bibliyometrik analiz yöntemi kullanılarak 741 yayından oluşan bir örneklem oluşturulmuştur. Bibliyometrik analiz için VOSViewer programı kullanılmış ve elde edilen veriler tablo, grafik ve görsel haritalar halinde görselleştirilmiştir. Bulgular, anahtar kelimelerle ilgili yayınların büyük çoğunluğunun 2021 yılında yayınlandığını göstermektedir. En çok alıntı yapılan yayın ise 2014 yılında Colomina ve Molina tarafından yazılmıştır. Toplamda 86 çalışmanın yapıldığı yayınların çoğu Amerika Birleşik Devletleri'ndedir. En çok alıntı yapılan kuruluş Florida Üniversitesi'dir. Kümeleme çalışmalarında uzaktan algılama, sensör, drone kelimeleri sıklıkla karşılan çalışma alt başlıklarıdır.

Kaynakça

  • Abdel-Basset, M., Chang, V., & Nabeeh, N. A. (2020). An intelligent framework using disruptive technologies for COVID-19 analysis. Technological Forecasting & Social Change, 163, 120431.
  • Alshamhi, S. H., Ma, O., Ansari, M. S., & Almalki, F. A. (2019). Survey on collaborative smart drones and internet of things for improving smartness of smart cities. IEEE Access, 7, 128125-128152.
  • Alvarado, E. (2023, November 5). Survey Snapshot: Spain's Drone Market. Retrieved from Drone Industry Insights: https://droneii.com/drone-companies-in-spain-drone-market
  • Altıntaş, O.A. (2023). Analysis of unmanned aerial vehicle systems occurrence reports from the safety management system perspective and scope of ICAO standards. Eskişehir Teknik Üniversitesi, Lisansüstü Eğitim Enstitüsü, Eskişehir. https://tez.yok.gov.tr/UlusalTezMerkezi/TezGosterkey=a0OMTmEd_3mfOBxT8SiBTIzaePYMbQEyFvTJuotgqKLBLfuI6rsN9LAdO9xMElRw.
  • Balasingam, M. (2017). Drones in medicine - the rise of machines. International Journal of Clinical Practice, 71(9), e12989.
  • Blyenburgh, P. v. (2021). RPAS The Global Perspective Volume 1. Retrieved from Remotely Piloted Systems The International Information & Reference Source: https://rps-info.com/publications/rpas-the-global-perspective_volume-1_2021_flipbook/
  • Carr, E. B. (2013). Unmanned aerial vehicles: Examining the safety, security, privacy and regulatory issues of integration into US airspace. National Centre for Policy Analysis (NCPA). Retrieved on September, 23(2013), 2014.
  • Colomina, I., & Molina, P. (2014). Unmanned aerial systems for photogrammetry and remote sensing: A review. ISPRS Journal of Photogrammetry and Remote Sensing, 92, 79-97.
  • Cruz, H., Eckert, M., Meneses, J., & Martínez, J.-F. (2016). Efficient forest fire detection index for application in unmanned aerial systems (UASs). Sensorns, 16(6), 893.
  • Ding, G., Wu, Q., Zhang, L., Lin, Y., Tsiftsis, T. A., & Yao, Y.-D. (2017). An amateur drone surveillance system based on the cognitive internet of things. IEEE Communications Magazine, 56(1), 29-35.
  • Dirik, D., Eryılmaz, İ. ve Erhan, T. (2023), Post-truth kavramı üzerine yapılan çalışmaların Vosviewer ile bibliyometrik analizi, Sosyal Mucit Academic Review, 4 (2), 164-188.
  • Dixit, A., & Jakhar, S. K. (2021). Airport capacity management: A review and bibliometric analysis. Journal of Air Transport Management, 91, 102010.
  • FAA. (2022, May 19). Safety Management System: SMS Explained. Retrieved from Federal Aviation Administration: https://www.faa.gov/about/initiatives/sms/explained
  • Forlani, G., Dall'Asta, E., Diotri, F., Cella, U. M., Roncella, R., & Santise, M. (2018). Quality assessment of DSMs produced from UAV flights georeferenced with on-board RTK positioning. Remote Sensing, 10(2), 311.
  • IATA. (2023). IATA Annual safety report executive summary and safety overview – 60th Edition. https://www.iata.org/contentassets/a8e49941e8824a058fee3f5ae0c005d9/safety-report-executive-and-safety-overview-2023.pdf
  • Naqvi, S. A.R, Hassan, S. A., Pervaiz, H., & Ni, Q. (2018). Drone-aided communication as a key enabler for 5G and resilient public safety networks. IEEE Communications Magazine, 56(1), 36-42.
  • Newman, M. E. (2004). Coauthorship networks and patterns of scientific collaboration. Proceedings of the national academy of sciences, 101(suppl_1), 5200-5205.
  • Perez, H., Tah, J. H., & Mosavi, A. (2019). Deep learning for detecting building defects using convolutional neural networks. Sensors, 19(16), 3556.
  • Pierdicca, R., Malinverni, E. S., Piccinini, F., Paolanti, M., Felicetti, A., & Zingaretti, P. (2018). Deep convolutional neural Network for automatic detection of damaged photovoltaic cells. Remote Sensing and Spatial Information Sciences, 42, 893-900.
  • Rosser, Jr, J. C., Vignesh, V., Terwilliger, B. A., & Parker, B. C. (2018). Surgical and medical applications of drones: A comprehensive review. Journal of The Society of Laparoscopis & Robotic Surgeons, 22(3).
  • Sandbrook, C. (2015). The social implications of using drones for biodiversity. Ambio, 44(Suppl 4), 636-647. Taha, B., & Shoufan, A. (2019). Machine learning-based drone detection and classification: state-of-the-art in research. IEEE Access, 7, 138669-138682.
  • Visser, M., Eck, N. J., & Waltman, L. (2021). Large-scale comparison of bibliographic data sources: Scopus, Web of Science, Dimensions, Crossref, and Microsoft Academic. Quantitative Science Studies, 2(1), 20-41.
  • Watss, A. C., Ambrosia, V. G., & Hinkley, E. A. (2012). Unmanned aircraft systems in remote sensing and scientific research: Classification and considerations of use. Remote Sensing, 4(6), 1671-1692.
  • Weibel, R. E., & Hansman, R. J. (2006). Safety considerations for operation of unmanned aerial vehicles in the national airspace system. Technical report, ICAT 2005-01.
  • Yang, H.-H., Chang, Y.-H., & Lin, C.-H. (2022). A combined approach for selecting drone management strategies based on the ICAO Safety Management System (SMS) components. Journal of Air Transport Management, 104, 102257.
  • Zeng, Z., Chen, P.-J., & Lew, A. A. (2020). From high-touch to high-tech: COVID-19 drives. Tourism Geographies, 22(3), 724-734.
Toplam 26 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Hava-Uzay Ulaşımı
Bölüm Araştırma Makaleleri
Yazarlar

Osman Atilla Altıntaş 0000-0001-7328-3409

Birsen Açıkel 0000-0002-6067-5697

Ugur Turhan 0000-0002-0653-0630

Yayımlanma Tarihi 29 Ağustos 2024
Gönderilme Tarihi 15 Mart 2024
Kabul Tarihi 14 Temmuz 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 6 Sayı: 2

Kaynak Göster

APA Altıntaş, O. A., Açıkel, B., & Turhan, U. (2024). Evaluation of The Studies on Unmanned Aircraft System Safety Management Systems with Bibliometric Analysis. Journal of Aviation Research, 6(2), 132-148. https://doi.org/10.51785/jar.1453011

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