A Bibliometric Analysis of Drone Technology in Healthcare Logistics

Authors

  • Koh Bo Yao Universiti Tun Hussein Onn Malaysia & Allnex Asia GBS Sdn Bhd
  • Mohamad Ali Selimin Universiti Tun Hussein Onn Malaysia

DOI:

https://doi.org/10.58915/aset.v5i1.2968

Keywords:

Bibliometric analysis, Drone, Emergency medical services, Healthcare, Unmanned aerial vehicle (UAV)

Abstract

The integration of drone technology into healthcare logistics has emerged as a strategic innovation to enhance the speed, accessibility, and resilience of medical supply chains, particularly in emergency and remote settings. Despite rapid technological progress, the intellectual structure and global research dynamics of this domain remain fragmented and insufficiently synthesized. This study conducts a comprehensive bibliometric analysis to map the evolution, thematic structure, and collaborative landscape of drone technology in healthcare logistics. Bibliographic data were retrieved from the Scopus database and refined through systematic screening, yielding 830 peer-reviewed journal articles published between 2016 and 2025. Data cleaning was performed using OpenRefine, while performance analysis and science mapping were conducted using the Scopus analyzer and VOSviewer. The findings reveal exponential publication growth, with more than 60% of outputs produced in the most recent 4 years. The United States, India, and China lead in productivity, while emergency medical services, unmanned aerial vehicles, and Internet of Things emerge as dominant research themes. The results demonstrate a rapidly consolidating, interdisciplinary field with strong international collaboration, highlighting its expanding role in advancing resilient, intelligent healthcare logistics systems.

References

[1] Stierlin, N., Risch, M., & Risch, L. Current advancements in drone technology for medical sample transportation. Logistics, vol 8, issue 4 (2024) pp.104.

[2] Supriya, M., Jeevitha, S., Pranathi, S. K., & Lokeshkumar, M. The wings of wellness: Autonomous medical delivery drones enhancing patient care and accessibility. 2024 Ninth International Conference on Science Technology Engineering and Mathematics (ICONSTEM), (2024) pp.1-6.

[3] Thomas, K. S., Jacob, J. J., & Chereddy, K. Autonomous drone for crisis zones. 2025 14th Mediterranean Conference on Embedded Computing (MECO), (2025) pp.1-8.

[4] De Silvestri, S., Capasso, P. J., Gargiulo, A., Molinari, S., & Sanna, A. Challenges for the routine application of drones in healthcare: A scoping review. Drones, vol 7, issue 12 (2023) pp.685.

[5] Braun, J., Gertz, S. D., Furer, A., Bader, T., Frenkel, H., Chen, J., ... & Nachman, D. The promising future of drones in prehospital medical care and its application to battlefield medicine. Journal of Trauma and Acute Care Surgery, vol 87, issue 1S (2019) pp.S28-S34.

[6] Al-Fowaih, A. M., Al-Shahrani, A. F., Al-Kathami, S. E., Al-Subaie, O. A., Al-Shashai, Z. O., Smaili, F. M., & Alharthi, K. A. AI-driven UAV path planning for efficient medical item delivery. 2025 IEEE Conference on Artificial Intelligence (CAI), (2025) pp.1417-1422.

[7] Mohammadiarvejeh, P., & Hu, G. Optimization of drone delivery for perishable healthcare products in disasters. IISE Annual Conference. Proceedings, (2022) pp.1-6.

[8] Law, C. T., Moenig, C., Jeilani, H., Jeilani, M., & Young, T. Transforming healthcare logistics and evaluating current use cases of UAVs (drones) as a method of transportation in healthcare to generate recommendations for the NHS to use drone technology at scale: a narrative review. BMJ Innovations, vol 9, issue 3 (2023).

[9] Anbaroğlu, B. Drones in healthcare: An extended discussion on humanitarian logistics. Unmanned Aerial Vehicles in Civilian Logistics and Supply Chain Management, (2019) pp.86-114.

[10] Boeras, D. I., Collins, B. C., & Peeling, R. W. The use of drones in the delivery of rural healthcare. Revolutionizing Tropical Medicine: Point‐of‐Care Tests, New Imaging Technologies and Digital Health, (2019) pp.615-632.

[11] Saponi, M., Borboni, A., Adamini, R., Faglia, R., & Amici, C. Embedded payload solutions in UAVs for medium and small package delivery. Machines, vol 10, issue 9 (2022) pp.737.

[12] Babu, J. C., Venkatesh, C., Nuka, M. R., & Kumar, A. Delivery of medicine using a UAV powered by the KK copter 2.1. 15 flight controller. 2025 2nd International Conference On Multidisciplinary Research and Innovations in Engineering (MRIE), (2025) pp.17-22.

[13] Al-Alawi, A. I., & AlEnezi, A. A. Investigating the effectiveness of drone technology in delivering medical supplies to remote or underserved areas. 2024 International Conference on IT Innovation and Knowledge Discovery (ITIKD), (2025) pp.1-9.

[14] Ray, P. P., & Dash, D. Blockchain for IoT-based medical delivery drones: State of the art, issues, and future prospects. Blockchain Technology for Emerging Applications, (2022) pp.137-176.

[15] Rajamohan, K. Review of medical drones in healthcare applications. Internet of Drones, (2023) pp.59-74.

[16] Verbeek, A., Debackere, K., Luwel, M., & Zimmermann, E. Measuring progress and evolution in science and technology–i: The multiple uses of bibliometric indicators. International Journal of Management Reviews, vol 4, issue 2 (2002) pp.179-211.

[17] Assyakur, D. S., & Rosa, E. M. Spiritual leadership in healthcare: A bibliometric analysis. Jurnal Aisyah: Jurnal Ilmu Kesehatan, vol 7, issue 2 (2022) pp.355-362.

[18] Alves, J. L., Borges, I. B., & Nadae, J. D. Sustainability in complex projects of civil construction: Bibliometric and bibliographic review. Gestão & Produção, vol 28 (2021) pp.e5389.

[19] Wu, Y. C. J., & Wu, T. A decade of entrepreneurship education in the Asia Pacific for future directions in theory and practice. Management Decision, vol 55, issue 7 (2017) pp.1333-1350.

[20] Fahimnia, B., Sarkis, J., & Davarzani, H. Green supply chain management: A review and bibliometric analysis. International Journal of Production Economics, vol 162 (2015) pp.101-114.

[21] Di Stefano, G., Peteraf, M., & Verona, G. Dynamic capabilities deconstructed: A bibliographic investigation into the origins, development, and future directions of the research domain. Industrial and Corporate Change, vol 19, issue 4 (2010) pp.1187-1204.

[22] Khiste, G. P., & Paithankar, R. R. Analysis of bibliometric term in Scopus. International Journal of Library Science and Information Management (IJLSIM), vol 3, issue 3 (2017) pp.81-88.

[23] Al-Khoury, A., Hussein, S. A., Abdulwhab, M., Aljuboori, Z. M., Haddad, H., Ali, M. A., ... & Flayyih, H. H. Intellectual capital history and trends: A bibliometric analysis using Scopus database. Sustainability, vol 14, issue 18 (2022) pp.11615.

[24] Gu, D., Li, T., Wang, X., Yang, X., & Yu, Z. Visualizing the intellectual structure and evolution of electronic health and telemedicine research. International Journal of Medical Informatics, vol 130 (2019) pp.103947.

[25] Van Eck, N. J., & Waltman, L. Citation-based clustering of publications using CitNetExplorer and VOSviewer. Scientometrics, vol 111, issue 2 (2017) pp.1053-1070.

[26] Van Eck, N. J., & Waltman, L. Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, vol 84, issue 2 (2010) pp.523-538.

[27] Appio, F. P., Cesaroni, F., & Di Minin, A. Visualizing the structure and bridges of the intellectual property management and strategy literature: A document co-citation analysis. Scientometrics, vol 101, issue 1 (2014) pp.623-661.

[28] Van Eck, N. J., & Waltman, L. Bibliometric mapping of the computational intelligence field. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, vol 15, issue 05 (2007) pp.625-645.

[29] Chamola, V., Hassija, V., Gupta, V., & Guizani, M. A comprehensive review of the COVID-19 pandemic and the role of IoT, drones, AI, blockchain, and 5G in managing its impact. IEEE Access, vol 8 (2020) pp.90225-90265.

[30] Park, J., Samarakoon, S., Bennis, M., & Debbah, M. Wireless network intelligence at the edge. Proc. IEEE, vol 107, issue 11 (2019) pp.2204-2239.

[31] Olasveengen, T. M., Semeraro, F., Ristagno, G., Castren, M., Handley, A., Kuzovlev, A., ... & Perkins, G. D. European resuscitation council guidelines 2021: Basic life support. Resuscitation, vol 161 (2021) pp.98-114.

[32] Gupta, M., Abdelsalam, M., Khorsandroo, S., & Mittal, S. Security and privacy in smart farming: Challenges and opportunities. IEEE Access, vol 8 (2020) pp.34564-34584.

[33] Behroozpour, B., Sandborn, P. A., Wu, M. C., & Boser, B. E. Lidar system architectures and circuits. IEEE Communications Magazine, vol 55, issue 10 (2017) pp.135-142.

[34] Tanwar, S., Bhatia, Q., Patel, P., Kumari, A., Singh, P. K., & Hong, W. C. Machine learning adoption in blockchain-based smart applications: The challenges, and a way forward. IEEE Access, vol 8 (2019) pp.474-488.

[35] Moshref-Javadi, M., & Winkenbach, M. Applications and research avenues for drone-based models in logistics: A classification and review. Expert Systems with Applications, vol 177 (2021) pp.114854.

[36] Rabta, B., Wankmüller, C., & Reiner, G. A drone fleet model for last-mile distribution in disaster relief operations. International Journal of Disaster Risk Reduction, vol 28 (2018) pp.107-112.

[37] Ferrag, M. A., Friha, O., Maglaras, L., Janicke, H., & Shu, L. Federated deep learning for cyber security in the internet of things: Concepts, applications, and experimental analysis. IEEE Access, vol 9 (2021) pp.138509-138542.

[38] Cohen, O., Zhu, B., & Rosen, M. S. MR fingerprinting deep reconstruction network (DRONE). Magnetic Resonance in Medicine, vol 80, issue 3 (2018) pp.885-894.

Downloads

Published

2026-06-02

How to Cite

Bo Yao, K., & Selimin, M. A. (2026). A Bibliometric Analysis of Drone Technology in Healthcare Logistics. Advanced and Sustainable Technologies (ASET), 5(1), 50–63. https://doi.org/10.58915/aset.v5i1.2968

Issue

Section

Articles

Similar Articles

<< < 3 4 5 6 7 8 9 > >> 

You may also start an advanced similarity search for this article.