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01-12-2023 | COVID-19 | Review

Survey on Path Planning for UAVs in Healthcare Missions

Authors: Ahmad Merei, Hamid Mcheick, Alia Ghaddar

Published in: Journal of Medical Systems | Issue 1/2023

Abstract

This article presents a comprehensive review of the state-of-the-art applications and methodologies related to the use of unmanned aerial vehicles (UAVs) in the healthcare sector, with a particular focus on path planning. UAVs have gained remarkable attention in healthcare during the outbreak of COVID-19, and this study explores their potential as a viable option for medical transportation. The survey categorizes existing studies by mission type, challenges addressed, and performance metrics to provide a clearer picture of the path planning problems and potential directions for future research. It highlights the importance of addressing the path planning problem and the challenges that UAVs may face during their missions, including the UAV delivery range limitation, and discusses recent solutions in this field. The study concludes by encouraging researchers to conduct their studies in a realistic environment to reveal UAVs’ real potential, usability, and feasibility in the healthcare domain.

CAWTHORNE, D., FREDERIKSEN, M.H.: Using the public perception of drones to design for explicability

Singh, A., Shetty, R., Kale, T., Yadav, S., Iyer, R.: Artificial intelligence based drone for healthcare. International Journal of Recent Advances in Multidisciplinary Topics 2(4), 140–144 (2021)

Yang, K., Shi, Y., Zhou, Y., Yang, Z., Fu, L., Chen, W.: Federated machine learning for intelligent iot via reconfigurable intelligent surface. IEEE Network 34(5), 16–22 (2020)CrossRef

Knoblauch, A.M., de la Rosa, S., Sherman, J., Blauvelt, C., Matemba, C., Maxim, L., Defawe, O.D., Gueye, A., Robertson, J., McKinney, J.: Bi-directional drones to strengthen healthcare provision: experiences and lessons from madagascar, malawi and senegal. BMJ global health 4(4), 001541 (2019)

Zailani, M.A.H., Sabudin, R.Z.A.R., Rahman, R.A., Saiboon, I.M., Ismail, A., Mahdy, Z.A.: Drone technology in maternal healthcare in malaysia: A narrative review. The Malaysian journal of pathology 43(2), 251–259 (2021)

G Peñaloza, E.A., A Oliveira, V., Cruvinel, P.E.: Using soft sensors as a basis of an innovative architecture for operation planning and quality evaluation in agricultural sprayers. Sensors 21(4), 1269 (2021)

Gallo, I.G., Martínez-Corbella, M., Sarro, R., Iovine, G., López-Vinielles, J., Hérnandez, M., Robustelli, G., Mateos, R.M., García-Davalillo, J.C.: An integration of uav-based photogrammetry and 3d modelling for rockfall hazard assessment: The cárcavos case in 2018 (spain). Remote Sensing 13(17), 3450 (2021)CrossRef

Alvear, O., Calafate, C.T., Zema, N.R., Natalizio, E., Hernández-Orallo, E., Cano, J.-C., Manzoni, P.: A discretized approach to air pollution monitoring using uav-based sensing. Mobile Networks and Applications 23(6), 1693–1702 (2018)CrossRef

Hong, L., Wang, Y., Du, Y., Chen, X., Zheng, Y.: Uav search-and-rescue planning using an adaptive memetic algorithm. Frontiers of Information Technology & Electronic Engineering 22(11), 1477–1491 (2021)CrossRef

10.

Hiebert, B., Nouvet, E., Jeyabalan, V., Donelle, L.: The application of drones in healthcare and health-related services in north america: A scoping review. Drones 4(3), 30 (2020)CrossRef

11.

Eichleay, M., Evens, E., Stankevitz, K., Parker, C.: Using the unmanned aerial vehicle delivery decision tool to consider transporting medical supplies via drone. Global Health: Science and Practice 7(4), 500–506 (2019)PubMed

12.

Phillips, J.: Medical unmanned aerial system for organ transplant delivery. California University of Pennsylvania (2019)

13.

Barnawi, A., Chhikara, P., Tekchandani, R., Kumar, N., Boulares, M.: A cnn-based scheme for covid-19 detection with emergency services provisions using an optimal path planning. Multimedia Systems, 1–15 (2021)

14.

Fakhrulddin, S.S., Gharghan, S.K.: An elderly first aid system based-fall detection and unmanned aerial vehicle. In: IOP Conference Series: Materials Science and Engineering, vol. 745, p. 012096 (2020). IOP Publishing

15.

Mukati, N., Namdev, N., Dilip, R., Hemalatha, N., Dhiman, V., Sahu, B.: Healthcare assistance to covid-19 patient using internet of things (iot) enabled technologies. Materials Today: Proceedings (2021)

16.

Nasajpour, M., Pouriyeh, S., Parizi, R.M., Dorodchi, M., Valero, M., Arabnia, H.R.: Internet of things for current covid-19 and future pandemics: An exploratory study. Journal of healthcare informatics research, 1–40 (2020)

17.

Munawar, H.S., Inam, H., Ullah, F., Qayyum, S., Kouzani, A.Z., Mahmud, M.: Towards smart healthcare: Uav-based optimized path planning for delivering covid-19 self-testing kits using cutting edge technologies. Sustainability 13(18), 10426 (2021)CrossRef

18.

Jones, R.W., Despotou, G.: Unmanned aerial systems and healthcare: Possibilities and challenges. In: 2019 14th IEEE Conference on Industrial Electronics and Applications (ICIEA), pp. 189–194 (2019). IEEE

19.

Azadi, S., Kazemi, R., Nedamani, H.R.: Chapter 10 - trajectory planning of tractor semitrailers, 429–478 (2021). https://doi.org/10.1016/B978-0-323-85659-1.00010-0

20.

Cabreira, T.M., Brisolara, L.B., Ferreira Jr, P.R.: Survey on coverage path planning with unmanned aerial vehicles. Drones 3(1), 4 (2019)CrossRef

21.

Majeed, A., Hwang, S.O.: A multi-objective coverage path planning algorithm for uavs to cover spatially distributed regions in urban environments. Aerospace 8(11), 343 (2021)CrossRef

22.

Nasr, S., Mekki, H., Bouallegue, K.: A multi-scroll chaotic system for a higher coverage path planning of a mobile robot using flatness controller. Chaos Solitons Fractals 118, 366–375 (2019)CrossRef

23.

Montanari, A., Kringberg, F., Valentini, A., Mascolo, C., Prorok, A.: Surveying areas in developing regions through context aware drone mobility. In: Proceedings of the 4th ACM Workshop on Micro Aerial Vehicle Networks, Systems, and Applications. DroNet’18, pp. 27–32. ACM, New York, NY, USA (2018). https://doi.org/10.1145/3213526.3213532.

24.

Samaniego, F., Sanchis, J., García-Nieto, S., Simarro, R.: Recursive rewarding modified adaptive cell decomposition (rr-macd): a dynamic path planning algorithm for uavs. Electronics 8(3), 306 (2019)CrossRef

25.

Coombes, M., Chen, W.-H., Liu, C.: Boustrophedon coverage path planning for uav aerial surveys in wind. In: 2017 International Conference on Unmanned Aircraft Systems (ICUAS), pp. 1563–1571 (2017). IEEE

26.

Samuel, V.M., Shehata, O.M., Morgan, E.-S.I.: Chaos generation for multi-robot 3d-volume coverage maximization. In: Proceedings of the 4th International Conference on Control, Mechatronics and Automation, pp. 36–40 (2016)

27.

Ghaddar, A., Merei, A.: Energy-aware grid based coverage path planning for uavs. In: Proceedings of the Thirteenth International Conference on Sensor Technologies and Applications SENSORCOMM, Nice, France, pp. 27–31 (2019)

28.

Ghaddar, A., Merei, A., Natalizio, E.: Pps: Energy-aware grid-based coverage path planning for uavs using area partitioning in the presence of nfzs. Sensors 20(13), 3742 (2020)PubMedPubMedCentralCrossRef

29.

Torres, M., Pelta, D.A., Verdegay, J.L., Torres, J.C.: Coverage path planning with unmanned aerial vehicles for 3d terrain reconstruction. Expert Systems with Applications 55, 441–451 (2016)CrossRef

30.

Cabreira, T.M., Di Franco, C., Ferreira, P.R., Buttazzo, G.C.: Energy-aware spiral coverage path planning for uav photogrammetric applications. IEEE Robotics and automation letters 3(4), 3662–3668 (2018)CrossRef

31.

Balampanis, F., Maza, I., Ollero, A.: In: Area Decomposition, Partition and Coverage with Multiple Remotely Piloted Aircraft Systems Operating in Coastal Regions, pp. 275–283 (2016). https://doi.org/10.1109/ICUAS.2016.7502602

32.

Balampanis, Fotios and Maza, Ivan and Ollero, Anibal: Area partition for coastal regions with multiple uas. Journal of Intelligent and Robotic Systems 88(2), 751–766 (2017). https://doi.org/10.1007/s10846-017-0559-9

33.

Li, M., Richards, A., Sooriyabandara, M.: Reliability-aware multi-uav coverage path planning using integer linear programming. In: UKRAS20 Conference:" Robots Into the Real World" Proceedings. EPSRC UK-RAS Network, pp. 15–17 (2020)

34.

Cho, D.-H., Ha, J.-S., Lee, S., Moon, S., Choi, H.-L.: Informative path planning and mapping with multiple uavs in wind fields, 269–283 (2018)

35.

Popovic, M., Hitz, G., Nieto, J., Sa, I., Siegwart, R., Galceran, E.: Online informative path planning for active classification using uavs. arXiv preprint arXiv:1609.08446 (2016)

36.

Popović, M., Vidal-Calleja, T., Hitz, G., Sa, I., Siegwart, R., Nieto, J.: Multiresolution mapping and informative path planning for uav-based terrain monitoring. In: 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 1382–1388 (2017). IEEE

37.

Popović, M., Vidal-Calleja, T., Hitz, G., Chung, J.J., Sa, I., Siegwart, R., Nieto, J.: An informative path planning framework for uav-based terrain monitoring. Autonomous Robots 44(6), 889–911 (2020)CrossRef

38.

Blanchard, A., Sapsis, T.: Informative path planning for extreme anomaly detection in environment exploration and monitoring. arXiv preprint arXiv:2005.10040 (2020)

39.

Krey, M., Seiler, R.: Usage and acceptance of drone technology in healthcare: exploring patients and physicians perspective. In: 52nd Hawaii International Conference on System Sciences, Grand Wailea HI, USA, 8-11 January 2019, pp. 4135–4144 (2019). HICSS

40.

Comtet, H.E., Johannessen, K.-A.: The moderating role of pro-innovative leadership and gender as an enabler for future drone transports in healthcare systems. International Journal of Environmental Research and Public Health 18(5), 2637 (2021)PubMedPubMedCentralCrossRef

41.

Cawthorne, D., Robbins-van Wynsberghe, A.: An ethical framework for the design, development, implementation, and assessment of drones used in public healthcare. Science and Engineering Ethics 26(5), 2867–2891 (2020)PubMedPubMedCentralCrossRef

42.

Jeyabalan, V., Nouvet, E., Meier, P., Donelle, L.: Context-specific challenges, opportunities, and ethics of drones for healthcare delivery in the eyes of program managers and field staff: a multi-site qualitative study. Drones 4(3), 44 (2020)CrossRef

43.

Zailani, M.A.H., Sabudin, R.Z.A.R., Rahman, R.A., Saiboon, I.M., Ismail, A., Mahdy, Z.A.: Drone for medical products transportation in maternal healthcare: A systematic review and framework for future research. Medicine 99(36) (2020)

44.

Talaie, T., Niederhaus, S., Villalongas, E., Scalea, J.: Innovating organ delivery to improve access to care: surgeon perspectives on the current system and future use of unmanned aircrafts. BMJ Innovations 7(1) (2021)

45.

Scalea, J.R., Restaino, S., Scassero, M., Blankenship, G., Bartlett, S.T., Wereley, N.: An initial investigation of unmanned aircraft systems (uas) and real-time organ status measurement for transporting human organs. IEEE journal of translational engineering in health and medicine 6, 1–7 (2018)CrossRef

46.

Balakrishnan, N., Devaraj, K., Rajan, S., Seshadri, G.: Transportation of organs using uav. In: Proc. Int. Conf. Ind. Eng. Oper. Management, vol. 3090 (2016)

47.

Al-Ayyad, M., Al-Ghraibah, A., Alkhatib, H.: Transportation of donated hearts by drone in comparison to road-bound vehicles in mexico city. The Open Biomedical Engineering Journal 13(1) (2019)

48.

Fakhrulddin, S.S., Gharghan, S.K., Al-Naji, A., Chahl, J.: An advanced first aid system based on an unmanned aerial vehicles and a wireless body area sensor network for elderly persons in outdoor environments. Sensors 19(13), 2955 (2019)PubMedPubMedCentralCrossRef

49.

Poljak, M., Šterbenc, A.: Use of drones in clinical microbiology and infectious diseases: current status, challenges and barriers. Clinical Microbiology and Infection 26(4), 425–430 (2020)PubMedCrossRef

50.

Ling, G., Draghic, N.: Aerial drones for blood delivery. Transfusion 59(S2), 1608–1611 (2019)PubMedCrossRef

51.

McCall, B.: Sub-saharan africa leads the way in medical drones. The Lancet 393(10166), 17–18 (2019)CrossRef

52.

Homier, V., Brouard, D., Nolan, M., Roy, M.-A., Pelletier, P., McDonald, M., de Champlain, F., Khalil, E., Grou-Boileau, F., Fleet, R.: Drone versus ground delivery of simulated blood products to an urban trauma center: the montreal medi-drone pilot study. The journal of trauma and acute care surgery 90(3), 515 (2021)PubMedCrossRef

53.

Beck, S., Bui, T.T., Davies, A., Courtney, P., Brown, A., Geudens, J., Royall, P.G.: An evaluation of the drone delivery of adrenaline auto-injectors for anaphylaxis: Pharmacists’ perceptions, acceptance, and concerns. Drones 4(4), 66 (2020)CrossRef

54.

Nyaaba, A.A., Ayamga, M.: Intricacies of medical drones in healthcare delivery: Implications for africa. Technology in Society 66, 101624 (2021)

55.

Rosser Jr, J.C., Vignesh, V., Terwilliger, B.A., Parker, B.C.: Surgical and medical applications of drones: A comprehensive review. JSLS: Journal of the Society of Laparoendoscopic Surgeons 22(3) (2018)

56.

Khan, M.A., Alvi, B.A., Safi, A., Khan, I.U.: Drones for good in smart cities: A review. In: Proc. Int. Conf. Elect., Electron., Comput., Commun., Mech. Comput.(EECCMC), pp. 1–6 (2018)

57.

Laksham, K.B.: Unmanned aerial vehicle (drones) in public health: A swot analysis. Journal of family medicine and primary care 8(2), 342 (2019)PubMedPubMedCentralCrossRef

58.

Schierbeck, S., Hollenberg, J., Nord, A., Svensson, L., Nordberg, P., Ringh, M., Forsberg, S., Lundgren, P., Axelsson, C., Claesson, A.: Automated external defibrillators delivered by drones to patients with suspected out-of-hospital cardiac arrest. European Heart Journal 42(Supplement_1), 724–0656 (2021)

59.

Wankmüller, C., Truden, C., Korzen, C., Hungerländer, P., Kolesnik, E., Reiner, G.: Optimal allocation of defibrillator drones in mountainous regions. OR Spectrum 42(3), 785–814 (2020)CrossRef

60.

Boutilier, J.J., Brooks, S.C., Janmohamed, A., Byers, A., Buick, J.E., Zhan, C., Schoellig, A.P., Cheskes, S., Morrison, L.J., Chan, T.C.: Optimizing a drone network to deliver automated external defibrillators. Circulation 135(25), 2454–2465 (2017)PubMedPubMedCentralCrossRef

61.

Boutilier, J.J., Chan, T.C.: Response time optimization for drone-delivered automated external defibrillators. arXiv preprint arXiv:1908.00149 (2019)

62.

Cheskes, S., McLeod, S.L., Nolan, M., Snobelen, P., Vaillancourt, C., Brooks, S.C., Dainty, K.N., Chan, T.C., Drennan, I.R.: Improving access to automated external defibrillators in rural and remote settings: a drone delivery feasibility study. Journal of the American Heart Association 9(14), 016687 (2020)

63.

Pulver, A., Wei, R., Mann, C.: Locating aed enabled medical drones to enhance cardiac arrest response times. Prehospital Emergency Care 20(3), 378–389 (2016)PubMedCrossRef

64.

Claesson, A., Fredman, D., Svensson, L., Ringh, M., Hollenberg, J., Nordberg, P., Rosenqvist, M., Djarv, T., Österberg, S., Lennartsson, J.: Unmanned aerial vehicles (drones) in out-of-hospital-cardiac-arrest. Scandinavian journal of trauma, resuscitation and emergency medicine 24(1), 1–9 (2016)CrossRef

65.

Sarker, S., Jamal, L., Ahmed, S.F., Irtisam, N.: Robotics and artificial intelligence in healthcare during covid-19 pandemic: A systematic review. Robotics and autonomous systems 146, 103902 (2021)

66.

Mbunge, E., Chitungo, I., Dzinamarira, T.: Unbundling the significance of cognitive robots and drones deployed to tackle covid-19 pandemic: A rapid review to unpack emerging opportunities to improve healthcare in sub-saharan africa. Cognitive Robotics 1, 205–213 (2021)PubMedCentralCrossRef

67.

Euchi, J.: Do drones have a realistic place in a pandemic fight for delivering medical supplies in healthcare systems problems? Elsevier (2021)

68.

Khan, Z.H., Siddique, A., Lee, C.W.: Robotics utilization for healthcare digitization in global covid-19 management. International journal of environmental research and public health 17(11), 3819 (2020)PubMedPubMedCentralCrossRef

69.

Oigbochie, A., Odigie, E., Adejumo, B.: Importance of drones in healthcare delivery amid a pandemic: Current and generation next application. Open Journal of Medical Research (ISSN: 2734-2093) 2(1), 01–13 (2021)

70.

Alsarhan, A., Almalkawi, I.T., Kilani, Y.: New covid-19 tracing approach using machine learning and drones enabled wireless network. International Journal of Interactive Mobile Technologies 15(22) (2021)

71.

Kumar, A., Sharma, K., Singh, H., Naugriya, S.G., Gill, S.S., Buyya, R.: A drone-based networked system and methods for combating coronavirus disease (covid-19) pandemic. Future Generation Computer Systems 115, 1–19 (2021)PubMedCrossRef

72.

Karaca, Y., Cicek, M., Tatli, O., Sahin, A., Pasli, S., Beser, M.F., Turedi, S.: The potential use of unmanned aircraft systems (drones) in mountain search and rescue operations. The American journal of emergency medicine 36(4), 583–588 (2018)PubMedCrossRef

73.

Doherty, P., Rudol, P.: A uav search and rescue scenario with human body detection and geolocalization. In: Australasian Joint Conference on Artificial Intelligence, pp. 1–13 (2007). Springer

74.

Câmara, D.: Cavalry to the rescue: Drones fleet to help rescuers operations over disasters scenarios. In: 2014 IEEE Conference on Antenna Measurements & Applications (CAMA), pp. 1–4 (2014). IEEE

75.

Mersheeva, V., Friedrich, G.: Routing for continuous monitoring by multiple micro avs in disaster scenarios, 588–593 (2012)

76.

Cui, J.Q., Phang, S.K., Ang, K.Z., Wang, F., Dong, X., Ke, Y., Lai, S., Li, K., Li, X., Lin, F.: Drones for cooperative search and rescue in post-disaster situation. In: 2015 IEEE 7th International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM), pp. 167–174 (2015). IEEE

77.

Wimberley, B.: The use of drones in Healthcare. Roche Diagnostics International AG (2021). https://healthcaretransformers.com/healthcare-business/drones-healthcare/

78.

Graboyes, R.F., Skorup, B.: Medical drones in the united states and a survey of technical and policy challenges. Mercatus Center Policy Brief (2020)

79.

Shruthi, B., Manasa, K., Lakshmi, R.: Survey on challenges and future scope of iot in healthcare and agriculture. International Journal of Computer Science and Mobile Computing 8(1), 21–26 (2019)

80.

Ersson, L., Olsson, E.: Drones to the Rescue: A literary study of Unmanned Aerial Systems within healthcare (2020)

81.

Allan-Matheson, D.: Unmanned aerial vehicles in healthcare: Now and for the future–investing into emerging technology for rapid vaccination delivery in healthcare, globally and especially in rural africa (2018)

82.

Sachan, D.: The age of drones: what might it mean for health? Lancet (London, England) 387(10030), 1803–1804 (2016)PubMedCrossRef

83.

Ingham, J.: Drones: Could they be used to deliver blood? BBC (2020). https://www.bbc.com/news/av/uk-england-hampshire-50960710

84.

Ayyappaa, N., Raj, A.Y., Adithya, A., Murali, R., Vinodh, A.: Autonomous drone for efficacious blood conveyance. In: 2019 4th International Conference on Robotics and Automation Engineering (ICRAE), pp. 99–103 (2019). IEEE

85.

Wen, T., Zhang, Z., Wong, K.K.: Multi-objective algorithm for blood supply via unmanned aerial vehicles to the wounded in an emergency situation. PloS one 11(5), 0155176 (2016)CrossRef

86.

Amukele, T.K., Hernandez, J., Snozek, C.L., Wyatt, R.G., Douglas, M., Amini, R., Street, J.: Drone transport of chemistry and hematology samples over long distances. American journal of clinical pathology 148(5), 427–435 (2017)PubMedCrossRef

87.

Amukele, T., Ness, P.M., Tobian, A.A., Boyd, J., Street, J.: Drone transportation of blood products. Transfusion 57(3), 582–588 (2017)PubMedCrossRef

88.

WHO: Coronavirus (COVID-19) Dashboard (2022). https://covid19.who.int/

89.

Dutta, P.K., Mitra, S.: Application of agricultural drones and iot to understand food supply chain during post covid-19. Agricultural Informatics: Automation Using the IoT and Machine Learning, 67–87 (2021)

90.

Estrada, M.R., Arturo, M.: The uses of drones in case of massive epidemics contagious diseases relief humanitarian aid: Wuhan-covid-19 crisis. Available at SSRN (2020)

91.

Lamptey, E., Serwaa, D.: The use of zipline drones technology for covid-19 samples transportation in ghana. HighTech and Innovation Journal 1(2), 67–71 (2020)CrossRef

92.

Ghaddar, A., Merei, A.: Eaoa: Energy-aware grid-based 3d-obstacle avoidance in coverage path planning for uavs. Future Internet 12(2), 29 (2020)CrossRef

93.

Pinheiro, M.A., Liu, M., Wan, Y., Dogan, A.: On the analysis of on-board sensing and off-board sensing through wireless communication for uav path planning in wind fields. In: AIAA Scitech 2019 Forum, p. 2131 (2019)

94.

Kim, S.-H., Padilla, G.E.G., Kim, K.-J., Yu, K.-H.: Flight path planning for a solar powered uav in wind fields using direct collocation. IEEE Transactions on Aerospace and Electronic Systems 56(2), 1094–1105 (2019)CrossRef

95.

Chen, H., Lu, P., Xiao, C.: Dynamic obstacle avoidance for uavs using a fast trajectory planning approach. In: 2019 IEEE International Conference on Robotics and Biomimetics (ROBIO), pp. 1459–1464 (2019). IEEE

96.

Safwat, N.E.-D., Hafez, I.M., Newagy, F.: 3d placement of a new tethered uav to uav relay system for coverage maximization. Electronics 11(3), 385 (2022)CrossRef

97.

Wang, Y., Zhu, X., Xu, L.: Flight path optimization for uavs to provide location service to ground targets. In: 2020 IEEE Wireless Communications and Networking Conference (WCNC), pp. 1–6 (2020). IEEE

98.

Wu, X., Bai, W., Xie, Y., Sun, X., Deng, C., Cui, H.: A hybrid algorithm of particle swarm optimization, metropolis criterion and rts smoother for path planning of uavs. Applied Soft Computing 73, 735–747 (2018)CrossRef

99.

Yang, H., Zhang, J., Song, S., Lataief, K.B.: Connectivity-aware uav path planning with aerial coverage maps. In: 2019 IEEE Wireless Communications and Networking Conference (WCNC), pp. 1–6 (2019). IEEE

100.

Shao, X.-X., Gong, Y.-J., Zhan, Z.-H., Zhang, J.: Bipartite cooperative coevolution for energy-aware coverage path planning of uavs. IEEE Transactions on Artificial Intelligence 3(1), 29–42 (2021)CrossRef

101.

Zhan, C., Hu, H., Sui, X., Liu, Z., Niyato, D.: Completion time and energy optimization in the uav-enabled mobile-edge computing system. IEEE Internet of Things Journal 7(8), 7808–7822 (2020)CrossRef

102.

Wang, H., Wang, J., Ding, G., Chen, J., Gao, F., Han, Z.: Completion time minimization with path planning for fixed-wing uav communications. IEEE Transactions on Wireless Communications 18(7), 3485–3499 (2019)CrossRef

103.

Carrillo-Larco, R., Moscoso-Porras, M., Taype-Rondan, A., Ruiz-Alejos, A., Bernabe-Ortiz, A.: The use of unmanned aerial vehicles for health purposes: a systematic review of experimental studies. Global health, epidemiology and genomics 3 (2018)

104.

Pathak, P., Damle, M., Pal, P.R., Yadav, V.: Humanitarian impact of drones in healthcare and disaster management. Int. J. Recent Technol. Eng 7(5), 201–205 (2019)

105.

Clark, D.G., Ford, J.D., Tabish, T.: What role can unmanned aerial vehicles play in emergency response in the arctic: A case study from canada. PLoS One 13(12), 0205299 (2018)CrossRef

106.

Sigari, C., Biberthaler, P.: Medical drones: Disruptive technology makes the future happen. Der Unfallchirurg 124(12), 974–976 (2021)PubMedPubMedCentralCrossRef

107.

Magnusson, S., Hagerfors, P.P.: Drone deliveries of medical goods in urban healthcare. Master’s thesis (2019)

108.

Todd, C.A., Lutfi, A., Copiaco, A., Agarwal, V., Afsari, K., Johnathon, C., Okafor, O., Ayad, M.: Towards an autonomous, unmanned aerial vehicle for indoor flight in healthcare; a review of research challenges and approaches (2015)

109.

Kunovjanek, M., Wankmüller, C.: Containing the covid-19 pandemic with drones-feasibility of a drone enabled back-up transport system. Transport Policy 106, 141–152 (2021)PubMedPubMedCentralCrossRef

110.

Aggarwal, S., Kumar, N., Alhussein, M., Muhammad, G.: Blockchain-based uav path planning for healthcare 4.0: Current challenges and the way ahead. IEEE Network 35(1), 20–29 (2021)

111.

Ackerman, E., Strickland, E.: Medical delivery drones take flight in east africa. IEEE Spectrum 55(1), 34–35 (2018)CrossRef

112.

Konert, A., Smereka, J., Szarpak, L.: The use of drones in emergency medicine: practical and legal aspects. Emergency medicine international (2019)

113.

Kramar, V.: Uas (drone) in response to coronavirus. In: 2020 27th Conference of Open Innovations Association (FRUCT), pp. 90–100 (2020). IEEE

114.

Awad, A., Trenfield, S.J., Pollard, T.D., Ong, J.J., Elbadawi, M., McCoubrey, L.E., Goyanes, A., Gaisford, S., Basit, A.W.: Connected healthcare: Improving patient care using digital health technologies. Advanced Drug Delivery Reviews 178, 113958 (2021)

115.

Mateen, F.J., Leung, K.B., Vogel, A.C., Cissé, A.F., Chan, T.C.: A drone delivery network for antiepileptic drugs: a framework and modelling case study in a low-income country. Transactions of the Royal Society of Tropical Medicine and Hygiene 114(4), 308–314 (2020)PubMedPubMedCentralCrossRef

116.

Wang, N., Christen, M., Hunt, M.: Ethical considerations associated with“humanitarian drones”: A scoping literature review. Science and engineering ethics 27(4), 1–21 (2021)

117.

Scott, J., Scott, C.: Drone delivery models for healthcare. In: Proceedings of the 50th Hawaii International Conference on System Sciences (2017)

118.

Abid, A., Cheikhrouhou, S., Kallel, S., Jmaiel, M.: Temporal constraints in smart contract-based process execution: A case study of organ transfer by healthcare delivery drone (2021)

119.

Li, J., Goh, W., Jhanjhi, N.: A design of iot-based medicine case for the multi-user medication management using drone in elderly centre. Journal of Engineering Science and Technology 16(2), 1145–1166 (2021)

120.

Kumar, G.D., Jeeva, B.: Drone ambulance for outdoor sports. Asian J. Appl. Sci. and Technol 1, 44–49 (2017)

121.

Vazquez-Carmona, E.V., Vasquez-Gomez, J.I., Lozada, J.C.H., Antonio-Cruz, M.: Coverage path planning for spraying drones. arXiv preprint arXiv:2105.08743 (2021)

122.

Saeed, F., Mehmood, A., Majeed, M.F., Maple, C., Saeed, K., Khattak, M.K., Wang, H., Epiphaniou, G.: Smart delivery and retrieval of swab collection kit for covid-19 test using autonomous unmanned aerial vehicles. Physical Communication 48, 101373 (2021)

123.

Khan, S.I., Qadir, Z., Munawar, H.S., Nayak, S.R., Budati, A.K., Verma, K.D., Prakash, D.: Uavs path planning architecture for effective medical emergency response in future networks. Physical Communication 47, 101337 (2021)

124.

Bitar, A., Jamal, A., Sultan, H., Alkandari, N., El-Abd, M.: Medical drones system for amusement parks. In: 2017 IEEE/ACS 14th International Conference on Computer Systems and Applications (AICCSA), pp. 19–20 (2017). IEEE

125.

Singh, A., Kumar, P., Pachauri, K., Singh, K.: Drone ambulance. In: 2020 2nd International Conference on Advances in Computing, Communication Control and Networking (ICACCCN), pp. 705–708 (2020). IEEE

126.

Rangel, R.K.: Development of low cost medical drone, using cots equipment. In: 2021 IEEE Aerospace Conference (50100), pp. 1–12 (2021). IEEE

127.

Dhivya, A.J.A., Premkumar, J.: Quadcopter based technology for an emergency healthcare. In: 2017 Third International Conference on Biosignals, Images and Instrumentation (ICBSII), pp. 1–3 (2017). IEEE

128.

Sanjana, P., Prathilothamai, M.: Drone design for first aid kit delivery in emergency situation. In: 2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS), pp. 215–220 (2020). IEEE

129.

Kulp, P., Mei, N.: A framework for sensing radio frequency spectrum attacks on medical delivery drones. In: 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 408–413 (2020). IEEE

130.

Faramondi, L., Oliva, G., Ardito, L., Crescenzi, A., Caricato, M., Tesei, M., Muda, A.O., Setola, R.: Use of drone to improve healthcare efficiency and sustainability. In: 2020 43rd International Convention on Information, Communication and Electronic Technology (MIPRO), pp. 1783–1788 (2020). IEEE

131.

Nithyavathy, N., Pavithra, S., Naveen, M., Logesh, B., James, T.: Design and development of drone for healthcare. Int. J. Sci. Technol. Res 9(1), 2676–2680 (2020)

132.

Hii, M.S.Y., Courtney, P., Royall, P.G.: An evaluation of the delivery of medicines using drones. Drones 3(3), 52 (2019)CrossRef

133.

Amukele, T.K., Street, J., Carroll, K., Miller, H., Zhang, S.X.: Drone transport of microbes in blood and sputum laboratory specimens. Journal of clinical microbiology 54(10), 2622–2625 (2016)PubMedPubMedCentralCrossRef

134.

Nenni, M.E., Di Pasquale, V., Miranda, S., Riemma, S.: Development of a drone-supported emergency medical service. International Journal of Technology (IJTech) 11(4) (2020)

135.

Ullah, S., Kim, K.-I., Kim, K.H., Imran, M., Khan, P., Tovar, E., Ali, F.: Uav-enabled healthcare architecture: Issues and challenges. Future Generation Computer Systems 97, 425–432 (2019)CrossRef

136.

Wang, Z., Sheu, J.-B.: Vehicle routing problem with drones. Transportation research part B: methodological 122, 350–364 (2019)CrossRef

137.

Kim, S., Moon, I.: Traveling salesman problem with a drone station. IEEE Transactions on Systems, Man, and Cybernetics: Systems 49(1), 42–52 (2018)CrossRef

138.

Huang, H., Savkin, A.V., Huang, C.: Reliable path planning for drone delivery using a stochastic time-dependent public transportation network. IEEE Transactions on Intelligent Transportation Systems 22(8), 4941–4950 (2020)CrossRef

Title: Survey on Path Planning for UAVs in Healthcare Missions
Authors: Ahmad Merei
Hamid Mcheick
Alia Ghaddar
Publication date: 01-12-2023
Publisher: Springer US
Keyword: COVID-19
Published in: Journal of Medical Systems / Issue 1/2023
Print ISSN: 0148-5598
Electronic ISSN: 1573-689X
DOI: https://doi.org/10.1007/s10916-023-01972-x

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Survey on Path Planning for UAVs in Healthcare Missions

Abstract

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

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