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
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页数:18
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