Designing and Implementation of Weedinator -The  Agribot

Komal Ananda Palande; Dipali Jadhav; Kirti shamarav bhosale; Aishwarya Dnyandev Taware; Rituja Pradip Nimbalkar

doi:10.37628/ijra.v8i2.1496

Designing and Implementation of Weedinator -The Agribot

Komal Ananda Palande, Dipali Jadhav, Kirti shamarav bhosale, Aishwarya Dnyandev Taware, Rituja Pradip Nimbalkar

Abstract

Herbicides are often sprayed widely across the yard as part of a normal herbicide control method. Herbicides may release chemical residue that is bad on soil and plants if they are used inappropriately and persistently. When the use of image processing on farm for targeted farming in the detection procedure of handling weeds grows fascinating there are still some problems with computer dimensions
and power expenditure. One minicomputer that is cheaper and uses relatively little electricity is the Raspberry Pi, or Raspberry Pi. Processing pictures and weed dimension-fractal processing using Open CV library and C language programming can be performed using a desktop computer with the gratis
and open-source Linux operating system. The image with a dimension size of 128 × 128 pixels delivers the best fractal compute time in this study. Four milliseconds or so about. The Raspberry Pi is 0.04 times faster than a personal computer on average. With regard with operating a personal computer, owning a Raspberry Pi is simpler and uses fewer watts of electricity.

Keywords

Weeds Detection, Computer Vision, Fractal, Raspberry Pi

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References

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DOI: https://doi.org/10.37628/ijra.v8i2.1496

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