@article{
 title = {Drones in agriculture: A review and bibliometric analysis},
 type = {article},
 year = {2022},
 keywords = {Bibliometrics,Drones,Internet of Things,Precision agriculture,UAV},
 pages = {107017},
 volume = {198},
 month = {7},
 publisher = {Elsevier},
 day = {1},
 id = {836648aa-2cf4-30cf-9cae-ce9b86c25c01},
 created = {2024-12-06T10:30:28.906Z},
 accessed = {2024-12-06},
 file_attached = {true},
 profile_id = {f1f70cad-e32d-3de2-a3c0-be1736cb88be},
 group_id = {5ec9cc91-a5d6-3de5-82f3-3ef3d98a89c1},
 last_modified = {2024-12-06T10:30:33.016Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 folder_uuids = {1619600c-2adf-4216-9e4c-d260d584753e},
 private_publication = {false},
 abstract = {Drones, also called Unmanned Aerial Vehicles (UAV), have witnessed a remarkable development in recent decades. In agriculture, they have changed farming practices by offering farmers substantial cost savings, increased operational efficiency, and better profitability. Over the past decades, the topic of agricultural drones has attracted remarkable academic attention. We therefore conduct a comprehensive review based on bibliometrics to summarize and structure existing academic literature and reveal current research trends and hotspots. We apply bibliometric techniques and analyze the literature surrounding agricultural drones to summarize and assess previous research. Our analysis indicates that remote sensing, precision agriculture, deep learning, machine learning, and the Internet of Things are critical topics related to agricultural drones. The co-citation analysis reveals six broad research clusters in the literature. This study is one of the first attempts to summarize drone research in agriculture and suggest future research directions.},
 bibtype = {article},
 author = {Rejeb, Abderahman and Abdollahi, Alireza and Rejeb, Karim and Treiblmaier, Horst},
 doi = {10.1016/J.COMPAG.2022.107017},
 journal = {Computers and Electronics in Agriculture}
}

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