Paper Contents
Abstract
Weed detection is an important task in precision agriculture, as it can help farmers to reduce herbicide use, increase crop yields, and minimize the environmental impact of agriculture. In this paper, we present a system for weed detection using image processing and Arduino. The system consists of a camera mounted on a mobile platform, which captures images of crops and weeds in the field. The images are then processed using a computer vision algorithm to detect and classify weeds based on their color and shape characteristics. The system is controlled by an Arduino microcontroller, which communicates with the camera and processes the image data. The results of the weed detection algorithm are displayed on a graphical user interface (GUI), which allows farmers to visualize and analyze the data. We tested the system on a variety of crops and weed species, and found that it achieved a high level of accuracy and reliability in detecting weeds. The system has the potential to improve the efficiency and sustainability of agriculture, by reducing the use of herbicides and promoting more targeted and precise weed control. It is also useful for researchers and developers who are interested in exploring the potential of computer vision and Arduino in the field of precision agriculture and weed management.
Copyright
Copyright © 2023 S.Nithyadevi. This is an open access article distributed under the Creative Commons Attribution License.
