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Time Optimization of Unmanned Aerial Vehicles Using an Augmented Path

Author

Listed:
  • Abdul Quadir Md

    (Vellore Institute of Technology (VIT), School of Computer Science and Engineering, Chennai 632002, India)

  • Divyank Agrawal

    (Vellore Institute of Technology (VIT), School of Computer Science and Engineering, Chennai 632002, India)

  • Monark Mehta

    (Vellore Institute of Technology (VIT), School of Computer Science and Engineering, Chennai 632002, India)

  • Arun Kumar Sivaraman

    (Vellore Institute of Technology (VIT), School of Computer Science and Engineering, Chennai 632002, India)

  • Kong Fah Tee

    (School of Engineering, University of Greenwich, Kent ME4 4TB, UK)

Abstract

With the pandemic gripping the entire humanity and with uncertainty hovering like a black cloud over all our future sustainability and growth, it became almost apparent that though the development and advancement are at their peak, we are still not ready for the worst. New and better solutions need to be applied so that we will be capable of fighting these conditions. One such prospect is delivery, where everything has to be changed, and each parcel, which was passed people to people, department to department, has to be made contactless throughout with as little error as possible. Thus, the prospect of drone delivery and its importance came around with optimization of the existing system for making it useful in the prospects of delivery of important items like medicines, vaccines, etc. These modular AI-guided drones are faster, efficient, less expensive, and less power-consuming than the actual delivery.

Suggested Citation

  • Abdul Quadir Md & Divyank Agrawal & Monark Mehta & Arun Kumar Sivaraman & Kong Fah Tee, 2021. "Time Optimization of Unmanned Aerial Vehicles Using an Augmented Path," Future Internet, MDPI, vol. 13(12), pages 1-14, November.
  • Handle: RePEc:gam:jftint:v:13:y:2021:i:12:p:308-:d:691138
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    References listed on IDEAS

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    Full references (including those not matched with items on IDEAS)

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