The use of drones in mountain search and rescue (GOPR) in Poland - possibilities and limitations

• Autorzy: Domański Roman

Identyfikatory

DOI

10.17270/J.LOG.2022.754

• Języki publikacji: EN

Abstrakty

EN

Background: Distribution using drones is treated as a developmental and promising form of transport in the future - an innovative way of moving about. The literature review showed a lack of a comprehensive and holistic assessment of the phenomenon of the use of drones in mountain search and rescue in Poland, a research gap. The aim of the article is to perform a quantitative and qualitative assessment of this issue, acquiring new knowledge about the basics of phenomena and observable facts (cognitive aspect). Methods: The subject of the study are drones. The scope of the study covers only the mountain search and rescue in Poland. The entities under study are central branches of Mountain Volunteer Search and Rescue (GOPR). The study used the method of an in-depth direct interview carried out with mountain rescuers - drone pilots in GOPR. Results: The result of the analysis of the material from interviews is an assessment of the use of drones in search and rescue in Polish mountains: what drones are already used, in which mountain groups, how many are, how often they are used, what rescue tasks they perform, how many drone pilots there are, what competences they have, what opportunities and problems are associated with the operation of drones in mountainous terrain. Conclusions: Drones are already used in mountain search and rescue by GOPR – mainly for searching for people and monitoring avalanches. At the moment, the scale of the phenomenon is not very impressive. However, drones are treated as a developmental issue in GOPR. In addition to plans to increase the number of drones, GOPR is also considering the introduction of drones into other categories of rescue tasks as well as providing the current fleet with new additional equipment. The main barriers to further proliferation of drones in GOPR are legal, insurance, financial, and behavioral issues.

Słowa kluczowe

EN

drones; unmanned aerial vehicle; UAV; rescue; mountains; Poland; Mountain Volunteer Search and Rescue; GOPR

PL

drony; bezzałogowy statek powietrzny; góry; Polska; Górskie Ochotnicze Pogotowie Ratunkowe; GOPR

• Wydawca: Wyższa Szkoła Logistyki
• Czasopismo: LogForum
• Rocznik: 2022
• Tom: Vol. 18, no. 3
• Strony: 275--284
• Opis fizyczny: Bibliogr. 26 poz., tab.

Twórcy

autor

Domański Roman

• Poznan University of Technology, Faculty of Engineering Management, Institute of Logistics, Poznań, Poland

• https://orcid.org/0000-0001-5861-4978

Bibliografia

• 1. Abrahamsen, H.B., 2021, Use of an unmanned aerial vehicle to support situation assessment and decision-making in search and rescue operations in the mountains, Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine, 22 (1), 1-1, https://doi.org/10.1186/1757-7241-22-S1-P16
• 2. Abrahamsen, H.B., 2015, A remotely piloted aircraft system in major incident management: Concept and pilot, feasibility study, BMC Emergency Medicine, 15 (1), art. no. 12, 1-12, https://doi.org/10.1186/s12873-015-0036-3
• 3. Božić-Štulić, D., Marušić, Ž., Gotovac, S., 2019, Deep Learning Approach in Aerial Imagery for Supporting Land Search and Rescue Missions, International Journal of Computer Vision, 127 (9), 1256-1278, https://doi.org/10.1007/s11263-019-01177-1
• 4. Dousai, N.M.K., Lonearic, S., 2022, Detecting Humans in Search and Rescue Operations Based on Ensemble Learning, IEEE Access, 10, 26481-26492, https://doi.org/10.1109/ACCESS.2022.3156903
• 5. Gotovac, S., Zelenika, D., Marušić, Ž., Božić-štulić, D., 2020, Visual-based person detection for search-and-rescue with uas: Humans vs. machine learning algorithm, Remote Sensing, 12 (20), art. no. 3295, 1-25, https://doi.org/10.3390/rs12203295
• 6. Holzmann, P., Wankmüller, C., Globocnik, D., Schwarz, E.J., 2021, Drones to the rescue? Exploring rescue workers' behavioral intention to adopt drones in mountain rescue missions, International Journal of Physical Distribution and Logistics Management, 51 (4), 381-402, https://doi.org/10.1108/IJPDLM-01-2020-0025
• 7. Huang, H., Savkin, A.V., 2021, Path planning for a solar-powered UAV inspecting mountain sites for safety and rescue, Energies, 14 (7), art. no. 1968, 1-19, https://doi.org/10.3390/en14071968
• 8. Jurecka, M., Miziński, B., Niedzielski, T., 2019, Impact of boosting saturation on automatic human detection in imagery acquired by unmanned aerial vehicles, Journal of Applied Remote Sensing, 13 (4), art. no. 044525, https://doi.org/10.1117/1.JRS.13.044525
• 9. Lin, C.E., Lai, Y.-H., 2015, Quasi-ADS-B based UAV conflict detection and resolution to manned aircraft, Journal of Electrical and Computer Engineering, 2015, art. no. 297859, 1-12, https://doi.org/10.1155/2015/297859
• 10. Liu, Y., Liu, S., Xu, J., Wang, Y., Tan, G., Li, D., Fan, B., 2021, A New Clustering Algorithm Toward Building Segmentation From Aerial Images by Utilizing RGB-Component Differences, Earth and Space Science, 8 (8), art. no. e2020EA001571, 1-15, https://doi.org/10.1029/2020EA001571
• 11. McRae, J.N., Nielsen, B.M., Gay, C.J., Hunt, A.P., Nigh, A.D., 2021, Utilizing Drones to Restore and Maintain Radio Communication During Search and Rescue Operations, Wilderness and Environmental Medicine, 32 (1), 41-46, https://doi.org/10.1016/j.wem.2020.11.002
• 12. McRae, J.N., Gay, C.J., Nielsen, B.M., Hunt, A.P., 2019, Using an Unmanned Aircraft System (Drone) to Conduct a Complex High Altitude Search and Rescue Operation: A Case Study, Wilderness and Environmental Medicine, 30 (3), 287-290, https://doi.org/10.1016/j.wem.2019.03.004
• 13. Niedzielski, T., Jurecka, M., Miziński, B., Pawul, W., Motyl, T., 2021, First successful rescue of a lost person using the human detection system: A case study from Beskid Niski (SE Poland), Remote Sensing, 13 (23), art. no. 4903, 1-18, https://doi.org/10.3390/rs13234903
• 14. Niedzielski, T., Jurecka, M., 2018, Can Clouds Improve the Performance of Automated Human Detection in Aerial Images?, Pure and Applied Geophysics, 175 (9), 3343-3355, https://doi.org/10.1007/s00024-018-1931-9
• 15. Niedzielski, T., Jurecka, M., Stec, M., Wieczorek, M., Miziński, B., 2017, The nested k-means method: A new approach for detecting lost persons in aerial images acquired by unmanned aerial vehicles, Journal of Field Robotics, 34 (8), 1395-1406, https://doi.org/10.1002/rob.21720
• 16. Oz, I., Topcuoglu, H.R., Ermis, M., 2013, A meta-heuristic based three-dimensional path planning environment for unmanned aerial vehicles, SIMULATION, 89 (8), 903-920, https://doi.org/10.1177/0037549712456419
• 17. Patterson, T., McClean, S., Morrow, P., Parr, G., Luo, C., 2014, Timely autonomous identification of UAV safe landing zones, Image and Vision Computing, 32 (9), 568-578, https://doi.org/10.1016/j.imavis.2014.06.006
• 18. Qin, Y., Chen, Y., Qiao, H., Che, Z., Zhang, G., 2019, Design of dynamic track planning algorithm for disaster detection UAV, Hongwai yu Jiguang Gongcheng / Infrared and Laser Engineering, 48 (10), art. no. 1026003, 1-6, https://doi.org/10.3788/IRLA201948.1026003
• 19. Sambolek, S., Ivasic-Kos, M., 2021, Automatic person detection in search and rescue operations using deep CNN detectors, IEEE Access, 9, 37905-37922, https://doi.org/10.1109/ACCESS.2021.3063681
• 20. Van Veelen, M.J., Voegele, A., Rauch, S., Kaufmann, M., Brugger, H., Strapazzon, G., 2021, Covid-19 pandemic in mountainous areas: Impact, mitigation strategies, and new technologies in search and rescue operations, High Altitude Medicine and Biology, 22 (3), 335-341, https://doi.org/10.1089/ham.2020.0216
• 21. Wankmüller, C., Kunovjanek, M., Mayrgündter, S., 2021, Drones in emergency response - evidence from cross-border, multi-disciplinary usability tests, International Journal of Disaster Risk Reduction, 65, art. no. 102567, https://doi.org/10.1016/j.ijdrr.2021.102567
• 22. Wankmüller, C., Truden, C., Korzen, C., Hungerländer, P., Kolesnik, E., Reiner, G., 2020, Optimal allocation of defibrillator drones in mountainous regions, OR Spectrum, 42 (3), 785-814, https://doi.org/10.1007/s00291-020-00575-z
• 23. Xiang, J., Qing-Yi, H., An-Wen, W., Jun-Song, T., Chun-Yu, L., Chen, F., Ding-Yi, F., 2018, 2-OptACO: An Improvement of Ant Colony Optimization for UAV Path in Disaster Rescue, Journal of Information Science and Engineering, 34 (4), 1063-1077, https://doi.org/10.1109/NaNA.2017.16
• 24. Yunfeng, Z., Yang, Y., Yimin, D., Dailiang, Y., Zhoubo, W., 2021, UAV search and rescue positioning method based on sound wave communication, International Journal of Wireless and Mobile Computing, 21 (3), 265-273, https://doi.org/10.1504/IJWMC.2021.120909
• 25. Zhang, S., Zhang, M., Shao, J., Pu, J., 2022, Multi-UAVs 3D Path Planning Method Based on Random Strategy Search, Xitong Fangzhen Xuebao / Journal of System Simulation, 34 (6), 1286-1295, https://doi.org/10.16182/j.issn1004731x.joss.21-0112
• 26. Zhang, X., Hu, Y., Li, W., Pang, Q., Yuan, G., 2020, Multi-UAV fire fighting mission planning based on improved artificial bee colony algorithm, Zhongguo Guanxing Jishu Xuebao / Journal of Chinese Inertial Technology, 28 (4), 528-536, https://doi.org/10.13695/j.cnki.12-1222/o3.2020.04.018

Uwagi

PL

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).