Development of a Light-Weight Unmanned Aerial Vehicle for Precision Agriculture

被引:32
|
作者
Ukaegbu, Uchechi F. [1 ]
Tartibu, Lagouge K. [1 ]
Okwu, Modestus O. [1 ]
Olayode, Isaac O. [1 ]
机构
[1] Univ Johannesburg, Dept Mech & Ind Engn, POB 2028, ZA-2028 Johannesburg, South Africa
关键词
unmanned aerial vehicle (UAV); deep learning; Raspberry Pi 3; industry; 4; 0; precision agriculture; WEED DETECTION; DEEP; TECHNOLOGIES; NETWORKS; SMART;
D O I
10.3390/s21134417
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
This paper describes the development of a modular unmanned aerial vehicle for the detection and eradication of weeds on farmland. Precision agriculture entails solving the problem of poor agricultural yield due to competition for nutrients by weeds and provides a faster approach to eliminating the problematic weeds using emerging technologies. This research has addressed the aforementioned problem. A quadcopter was built, and components were assembled with light-weight materials. The system consists of the electric motor, electronic speed controller, propellers, frame, lithium polymer (li-po) battery, flight controller, a global positioning system (GPS), and receiver. A sprayer module which consists of a relay, Raspberry Pi 3, spray pump, 12 V DC source, water hose, and the tank was built. It operated in such a way that when a weed is detected based on the deep learning algorithms deployed on the Raspberry Pi, general purpose input/output (GPIO) 17 or GPIO 18 (of the Raspberry Pi) were activated to supply 3.3 V, which turned on a DC relay to spray herbicides accordingly. The sprayer module was mounted on the quadcopter and from the test-running operation conducted, broadleaf and grass weeds were accurately detected and the spraying of herbicides according to the weed type occurred in less than a second.
引用
收藏
页数:18
相关论文
共 50 条
  • [21] AerialFace: A Light Weight Framework for Unmanned Aerial Vehicle Face Recognition
    Ou, Zhiquan
    Yao, Liang
    Wu, Ting
    Liu, Fan
    2024 IEEE 18TH INTERNATIONAL CONFERENCE ON AUTOMATIC FACE AND GESTURE RECOGNITION, FG 2024, 2024,
  • [22] Development and Application of an Autonomous and Flexible Unmanned Aerial Vehicle for Precision Viticulture
    Matese, A.
    Primicerio, J.
    Di Gennaro, F.
    Fiorillo, E.
    Vaccari, F. P.
    Genesio, L.
    I INTERNATIONAL WORKSHOP ON VINEYARD MECHANIZATION AND GRAPE AND WINE QUALITY, 2013, 978
  • [23] A survey of unmanned aerial sensing solutions in precision agriculture
    Mukherjee, Anandarup
    Misra, Sudip
    Raghuwanshi, Narendra Singh
    JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, 2019, 148
  • [24] An overview of the use of Unmanned Aerial Vehicles for Precision Agriculture
    Hristov, Georgi
    Kinaneva, Diyana
    Georgiev, Georgi
    Zahariev, Plamen
    Kyuchukov, Petko
    PROCEEDINGS OF THE 2020 INTERNATIONAL CONFERENCE ON BIOMEDICAL INNOVATIONS AND APPLICATIONS (BIA 2020), 2020, : 137 - 140
  • [25] USE OF HIGH-RESOLUTION MULTISPECTRAL IMAGERY FROM AN UNMANNED AERIAL VEHICLE IN PRECISION AGRICULTURE
    Al-Arab, Manal
    Torres-Rua, Alfonso
    Ticlavilca, Andres
    Jensen, Austin
    McKee, Mac
    2013 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2013, : 2852 - 2855
  • [26] Selection of Unmanned Aerial Vehicle for Precision Agriculture with Multi-criteria Decision Making Algorithm
    Petkovics, Imre
    Simon, Janos
    Petkovics, Armin
    Covic, Zlatko
    2017 IEEE 15TH INTERNATIONAL SYMPOSIUM ON INTELLIGENT SYSTEMS AND INFORMATICS (SISY), 2017, : 151 - 155
  • [27] Small unmanned aerial system development and applications in precision agriculture and natural resource management
    Abd-Elrahman, Amr
    Quirk, Bruce
    Corbera, Jordi
    Habib, Ayman
    EUROPEAN JOURNAL OF REMOTE SENSING, 2019, 52 (01) : 504 - 505
  • [28] Precision Positioning of Unmanned Aerial Vehicle at Automatic Landing
    Shirokova, Elena I.
    Azarov, Andrey A.
    Wilson, Nina G.
    Shirokov, Igor B.
    PROCEEDINGS OF THE 2019 IEEE CONFERENCE OF RUSSIAN YOUNG RESEARCHERS IN ELECTRICAL AND ELECTRONIC ENGINEERING (EICONRUS), 2019, : 1065 - 1069
  • [29] Assessing the accuracy of mosaics from unmanned aerial vehicle (UAV) imagery for precision agriculture purposes in wheat
    D. Gómez-Candón
    A. I. De Castro
    F. López-Granados
    Precision Agriculture, 2014, 15 : 44 - 56
  • [30] Assessing the accuracy of mosaics from unmanned aerial vehicle (UAV) imagery for precision agriculture purposes in wheat
    Gomez-Candon, D.
    De Castro, A. I.
    Lopez-Granados, F.
    PRECISION AGRICULTURE, 2014, 15 (01) : 44 - 56