Computer vision based robotic weed control system for precision agriculture | IEEE Conference Publication | IEEE Xplore
Scheduled Maintenance: On Monday, 30 June, IEEE Xplore will undergo scheduled maintenance from 1:00-2:00 PM ET (1800-1900 UTC).
On Tuesday, 1 July, IEEE Xplore will undergo scheduled maintenance from 1:00-5:00 PM ET (1800-2200 UTC).
During these times, there may be intermittent impact on performance. We apologize for any inconvenience.

Computer vision based robotic weed control system for precision agriculture


Abstract:

India is primarily an agriculture-based country and its economy largely depends upon the agriculture. But, most of the crops grown by the farmer are affected by weeds. We...Show More

Abstract:

India is primarily an agriculture-based country and its economy largely depends upon the agriculture. But, most of the crops grown by the farmer are affected by weeds. Weed identification and control remains one of the most challenging tasks in agriculture. The most widely used methods for weed control is manual spraying of herbicides. But, this method has several negative impacts. Since hand labor is costly, an automated weed control system may be economically feasible. Although there have been many efforts to develop a system to control in-row weeds autonomously, no system is currently available for real-time field use. Further, the Onion is slow-growing, shallow-rooted crop that can suffer severe yield loss from weed competition. In order to overcome the above mentioned problems, the proposed system aims to develop a computer vision based robotic weed control system (WCS) for real-time control of weeds in onion fields. This system will be able to identify weeds and selectively spray right amount of the herbicide. The proposed WCS is an inexpensive and portable wireless system of handheld equipments which can be controlled remotely through a user friendly web interface. It is designed to automate the control of weeds and thus reduces the difficulties of farmers in maintaining the field. The proposed system is based on a combination of image processing, machine learning and internet of things (IoT).
Date of Conference: 13-16 September 2017
Date Added to IEEE Xplore: 04 December 2017
ISBN Information:
Conference Location: Udupi, India

Contact IEEE to Subscribe

References

References is not available for this document.