Machine vision detection of pests, diseases, and weeds: A review

  • Chiranjeevi Muppala Department of Electronics and Communication Engineering, VIT Chennai, India
  • Velmathi Guruviah Department of Electronics and Communication Engineering, VIT Chennai, India

Abstract

Most of mankind’s living and workspace have been or going to be blended with smart technologies like the Internet of Things. The industrial domain has embraced automation technology, but agriculture automation is still in its infancy since the espousal has high investment costs and little commercialization of innovative technologies due to reliability issues. Machine vision is a potential technique for surveillance of crop health which can pinpoint the geolocation of crop stress in the field. Early statistics on crop health can hasten prevention strategies such as pesticide, fungicide applications to reduce the pollution impact on water, soil, and air ecosystems. This paper condenses the proposed machine vision relate research literature in agriculture to date to explore various pests, diseases, and weeds detection mechanisms.

Keywords: Machine vision, Pest detection, Disease detection, Weed detection, Multispectral, Hyperspectral

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How to Cite
Muppala, C., and V. Guruviah. “Machine Vision Detection of Pests, Diseases, and Weeds: A Review”. Journal of Phytology, Vol. 12, Apr. 2020, pp. 9-19, doi:https://doi.org/10.25081/jp.2020.v12.6145.
Section
Review Article