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    IMPROVED PATHS FOR UAVS IN PESTICIDE SPRAYING WITH TERRAIN CONSIDERATION

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    https://airccse.com/agrij/papers/1121agrij03.pdf
    Permanent Link
    http://hdl.handle.net/11603/25030
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    • UMBC Faculty Collection
    • UMBC Information Systems Department
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    Author/Creator
    Pelosi, Michael
    Garcia, Connie
    Brown, Michael Scott
    Type of Work
    10 pages
    Text
    journal articles
    Citation of Original Publication
    Pelosi, Michael, Connie Garcia, and Michael Scott Brown. Agricultural Science: An International journal (AGRIJ) 1 (2022), no.1, pp 61-70. https://www.researchgate.net/profile/Michael-Brown-121/publication/356645304_Improved_Paths_for_UAVs_in_Pesticide_Spraying_with_Terrain_Consideration/links/61c60b3eb6b5667157a23a96/Improved-Paths-for-UAVs-in-Pesticide-Spraying-with-Terrain-Consideration.pdf
    Rights
    This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
    Subjects
    UAV
    Pesticide Spraying
    A* Algorithm
    Abstract
    This research was designed to investigate the use of unmanned aerial vehicles (UAV) in the agricultural industry. The application of pesticides on farmland by traditional methods such as spraying has several disadvantages including dangers of exposure for farm personnel, uneven application results and a greater rate of spray contaminating regions beyond the target area. UAVs potentially could improve the pesticide application process depending on the flight leg paths that attempt to maximize the weighted (by terrain area) cumulative sum of applications over segments of the application flights.


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    Albin O. Kuhn Library & Gallery
    University of Maryland, Baltimore County
    1000 Hilltop Circle
    Baltimore, MD 21250
    www.umbc.edu/scholarworks

    Contact information:
    Email: scholarworks-group@umbc.edu
    Phone: 410-455-3021


    If you wish to submit a copyright complaint or withdrawal request, please email mdsoar-help@umd.edu.