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Towards Smart Healthcare: UAV-Based Optimized Path Planning for Delivering COVID-19 Self-Testing Kits Using Cutting Edge Technologies

Author

Listed:
  • Hafiz Suliman Munawar

    (School of Built Environment, University of New South Wales, Sydney, NSW 2052, Australia)

  • Hina Inam

    (Department of Electrical Engineering, College of Electrical and Mechanical Engineering, National University of Sciences and Technology, Rawalpindi 44000, Pakistan)

  • Fahim Ullah

    (School of Civil Engineering and Surveying, University of Southern Queensland, Springfield, Ipswich, QLD 4300, Australia)

  • Siddra Qayyum

    (School of Built Environment, University of New South Wales, Sydney, NSW 2052, Australia)

  • Abbas Z. Kouzani

    (School of Engineering, Deakin University, Geelong, VIC 3216, Australia)

  • M. A. Parvez Mahmud

    (School of Engineering, Deakin University, Geelong, VIC 3216, Australia)

Abstract

Coronavirus Disease 2019 (COVID-19) has emerged as a global pandemic since late 2019 and has affected all forms of human life and economic developments. Various techniques are used to collect the infected patients’ sample, which carries risks of transferring the infection to others. The current study proposes an AI-powered UAV-based sample collection procedure through self-collection kits delivery to the potential patients and bringing the samples back for testing. Using a hypothetical case study of Islamabad, Pakistan, various test cases are run where the UAVs paths are optimized using four key algorithms, greedy, intra-route, inter-route, and tabu, to save time and reduce carbon emissions associated with alternate transportation methods. Four cases with 30, 50, 100, and 500 patients are investigated for delivering the self-testing kits to the patients. The results show that the Tabu algorithm provides the best-optimized paths covering 31.85, 51.35, 85, and 349.15 km distance for different numbers of patients. In addition, the algorithms optimize the number of UAVs to be used in each case and address the studied cases patients with 5, 8, 14, and 71 UAVs, respectively. The current study provides the first step towards the practical handling of COVID-19 and other pandemics in developing countries, where the risks of spreading the infections can be minimized by reducing person-to-person contact. Furthermore, the reduced carbon footprints of these UAVs are an added advantage for developing countries that struggle to control such emissions. The proposed system is equally applicable to both developed and developing countries and can help reduce the spread of COVID-19 through minimizing the person-to-person contact, thus helping the transformation of healthcare to smart healthcare.

Suggested Citation

  • Hafiz Suliman Munawar & Hina Inam & Fahim Ullah & Siddra Qayyum & Abbas Z. Kouzani & M. A. Parvez Mahmud, 2021. "Towards Smart Healthcare: UAV-Based Optimized Path Planning for Delivering COVID-19 Self-Testing Kits Using Cutting Edge Technologies," Sustainability, MDPI, vol. 13(18), pages 1-21, September.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:18:p:10426-:d:638633
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    References listed on IDEAS

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    1. Merve Kayacı Çodur & Mustafa Yılmaz, 2020. "A time-dependent hierarchical Chinese postman problem," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(1), pages 337-366, March.
    2. Alexandros Nikitas & Kalliopi Michalakopoulou & Eric Tchouamou Njoya & Dimitris Karampatzakis, 2020. "Artificial Intelligence, Transport and the Smart City: Definitions and Dimensions of a New Mobility Era," Sustainability, MDPI, vol. 12(7), pages 1-19, April.
    3. Ullah, Fahim & Qayyum, Siddra & Thaheem, Muhammad Jamaluddin & Al-Turjman, Fadi & Sepasgozar, Samad M.E., 2021. "Risk management in sustainable smart cities governance: A TOE framework," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    4. Alessandra Buja & Matteo Paganini & Silvia Cocchio & Manuela Scioni & Vincenzo Rebba & Vincenzo Baldo, 2020. "Demographic and socio-economic factors, and healthcare resource indicators associated with the rapid spread of COVID-19 in Northern Italy: An ecological study," PLOS ONE, Public Library of Science, vol. 15(12), pages 1-13, December.
    5. J. Homolak & I. Kodvanj & D. Virag, 2020. "Preliminary analysis of COVID-19 academic information patterns: a call for open science in the times of closed borders," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 2687-2701, September.
    6. Fahim Ullah & Samad M. E. Sepasgozar & Changxin Wang, 2018. "A Systematic Review of Smart Real Estate Technology: Drivers of, and Barriers to, the Use of Digital Disruptive Technologies and Online Platforms," Sustainability, MDPI, vol. 10(9), pages 1-44, September.
    7. Samuel C. A. Pereira, 2021. "On the precision of information," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 30(3), pages 569-584, August.
    8. Hafiz Suliman Munawar & Fahim Ullah & Siddra Qayyum & Sara Imran Khan & Mohammad Mojtahedi, 2021. "UAVs in Disaster Management: Application of Integrated Aerial Imagery and Convolutional Neural Network for Flood Detection," Sustainability, MDPI, vol. 13(14), pages 1-22, July.
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