Smart sprayer project: Sensor-based selective herbicide application system

Lei Tian, B. Steward, L. Tang

Research output: Contribution to journalArticle

Abstract

The smart sprayer, a local-vision-sensor-based precision chemical application system, was developed and tested. The long-term objectives of this project were to develop new technologies to estimate weed density and size in real-time, to realize site-specific weed control, and to effectively reduce the amount of herbicide applied to major crop fields. This research integrated a real-time machine vision sensing system and individual nozzle controlling device with a commercial map-driven-ready herbicide sprayer to create an intelligent sensing and spraying system. The machine vision system was specially designed to work under outdoor variable lighting conditions. Multiple vision sensors were used to cover the target area. Instead of trying to identify each individual plant in the field, weed infestation conditions in each control zone (management zone) were detected. To increase the delivery accuracy, each individual spray nozzle was controlled separately. The integrated system was tested to evaluate the effectiveness and performance under varying commercial field conditions. Using the on-board differential GPS, geo-referenced chemical input maps (equivalent to weed maps) were also recorded in real-time. The maps generated with this system have been compared with other sensing and referencing systems.

Original languageEnglish (US)
Pages (from-to)73-80
Number of pages8
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume4203
DOIs
StatePublished - Jan 1 2000

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Keywords

  • Herbicide application rate
  • Machine-vision
  • Multiple sensors
  • Spray nozzle
  • Weed

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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