Paper
29 December 2000 Smart sprayer project: sensor-based selective herbicide application system
Lei F. Tian, Brian L. Steward, Lie Tang
Author Affiliations +
Proceedings Volume 4203, Biological Quality and Precision Agriculture II; (2000) https://doi.org/10.1117/12.411741
Event: Environmental and Industrial Sensing, 2000, Boston, MA, United States
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.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Lei F. Tian, Brian L. Steward, and Lie Tang "Smart sprayer project: sensor-based selective herbicide application system", Proc. SPIE 4203, Biological Quality and Precision Agriculture II, (29 December 2000); https://doi.org/10.1117/12.411741
Lens.org Logo
CITATIONS
Cited by 6 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Machine vision

Sensing systems

Sensors

Control systems

Cameras

Distance measurement

Image processing

RELATED CONTENT


Back to Top