Integrating Robotics and Computer Vision for Precision Agriculture: An Autonomous System for Weed Control and Plant Health Monitoring


Authors : Jonnala Sai Maneesh Kumar; Kunchala Krishna; Thota Venkata Vinay

Volume/Issue : Volume 8 - 2023, Issue 12 - December

Google Scholar : https://tinyurl.com/4n6v3ch3

Scribd : https://tinyurl.com/32uentsk

DOI : https://doi.org/10.5281/zenodo.10350494

Abstract : The creation of a novel robot created especially for agricultural situations is described in this study. While ensuring the security of the primary crop, the robot combines cutting-edge features, such as weed removal and plant health monitoring. The robot can precisely identify and classify various kinds of weeds and plants thanks to its 5DOF robotic arm, servo gripper, and state-of-the-art computer vision algorithms. A camera system also makes it possible to track plant health and find soil moisture. The robot is self-sufficient and runs on a 12V battery with efficient energy use. The suggested method for getting rid of weeds makes use of a robotic arm-mounted nozzle and a servo gripper for precision weed removal. Additionally, the robot can drive independently and avoid obstacles in diverse agricultural settings thanks to route identification employing the ground-breaking idea of pixel summation. Field experiments have shown the robot's effectiveness in lowering weed populations, enhancing plant growth, and collecting useful information on the health of plants and the moisture level of the soil. This robot has the potential to revolutionize the agricultural industry by reducing the demand for human labour and increasing productivity and sustainability in farming. This project benefits farmers, agricultural enterprises, and researchers in the field of agriculture by providing an effective and practical solution for weed eradication, plant health monitoring, and automation in agriculture.

Keywords : Computer Vision, 5 Degrees of Freedom, Weed Detection, Weed Classification, Weed Removal, Soil Moisture, Plant Health Monitor (PHM), Path Detection.

The creation of a novel robot created especially for agricultural situations is described in this study. While ensuring the security of the primary crop, the robot combines cutting-edge features, such as weed removal and plant health monitoring. The robot can precisely identify and classify various kinds of weeds and plants thanks to its 5DOF robotic arm, servo gripper, and state-of-the-art computer vision algorithms. A camera system also makes it possible to track plant health and find soil moisture. The robot is self-sufficient and runs on a 12V battery with efficient energy use. The suggested method for getting rid of weeds makes use of a robotic arm-mounted nozzle and a servo gripper for precision weed removal. Additionally, the robot can drive independently and avoid obstacles in diverse agricultural settings thanks to route identification employing the ground-breaking idea of pixel summation. Field experiments have shown the robot's effectiveness in lowering weed populations, enhancing plant growth, and collecting useful information on the health of plants and the moisture level of the soil. This robot has the potential to revolutionize the agricultural industry by reducing the demand for human labour and increasing productivity and sustainability in farming. This project benefits farmers, agricultural enterprises, and researchers in the field of agriculture by providing an effective and practical solution for weed eradication, plant health monitoring, and automation in agriculture.

Keywords : Computer Vision, 5 Degrees of Freedom, Weed Detection, Weed Classification, Weed Removal, Soil Moisture, Plant Health Monitor (PHM), Path Detection.

CALL FOR PAPERS


Paper Submission Last Date
31 - May - 2024

Paper Review Notification
In 1-2 Days

Paper Publishing
In 2-3 Days

Video Explanation for Published paper

Never miss an update from Papermashup

Get notified about the latest tutorials and downloads.

Subscribe by Email

Get alerts directly into your inbox after each post and stay updated.
Subscribe
OR

Subscribe by RSS

Add our RSS to your feedreader to get regular updates from us.
Subscribe