Development of a light-weight unmanned aerial vehicle for precision agriculture

Uchechi F. Ukaegbu, Lagouge K. Tartibu, Modestus O. Okwu, Isaac O. Olayode

Research output: Contribution to journalArticlepeer-review

28 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number4417
JournalSensors
Volume21
Issue number13
DOIs
Publication statusPublished - 1 Jul 2021

Keywords

  • Deep learning
  • Industry 4.0
  • Precision agriculture
  • Raspberry Pi 3
  • Unmanned aerial vehicle (UAV)

ASJC Scopus subject areas

  • Analytical Chemistry
  • Information Systems
  • Atomic and Molecular Physics, and Optics
  • Biochemistry
  • Instrumentation
  • Electrical and Electronic Engineering

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