A Software Development for Real Time Spray Control System in Herbicide Application

Year 2017, Volume: 1 Issue: 1, 13 - 19, 30.08.2017

Ömer Barış Özlüoymak , Ali Bolat Ali Bayat Emin Güzel

Abstract

Advances in different technologies,
such as high-resolution vision systems, innovative sensors and embedded
computing systems, are finding direct application in agriculture. In precision
farming, image analysis techniques can aid farmers in herbicide applications,
and thus lower the risk of soil and water pollution by reducing the amount of
chemicals applied. Optical sensors and computer vision, which can be used in
automated weed detection and control spray systems, are being used in recent
years extensively. A real-time auto tracking and determination system for weed
detection and spray on/off were designed, built and set up in the laboratory at
the Department of Agricultural Machinery and Technologies Engineering of
Çukurova University. In this study; to get the target images, a web camera,
mounted at a height of 50 cm above the target object was used. During the start
of the weed tracking operation, the web camera captured images of the
artificial weeds. Developed software, which could be reprogrammed and adjusted
according to the user preference, was created by using LabVIEW. Weed coverage
was determined from each image by using a “greenness method” in which the red,
green, and blue intensities of each pixel were compared. The sprayer nozzle was
turned ‘on’ or ‘off’ by using a data acquisition card and a relay card,
depending on the green color pixels of weeds. The sprayer valve opened the
nozzle when the camera detected the presence of weeds. Image processing
performance of this system, in where nozzle and camera were mounted at a
stationary position while weeds were on a movable belt, was tested at the
different speeds of conveyor belt consisted of an inverter drive system and 3
phase 4 pole electric motor. The laboratory performance evolution revealed that
the system could detect the weeds successfully and could be used to decrease
the herbicide quantity.

Keywords

Image processing, LabVIEW, Machine vision, Weed detection

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