Detection of Weed plant in Farm and Removing using Unmanned Ground Vehicle

• Main Authors: R, Sandeep Telkar, Yakkundimath, Rajesh, Thomas, Likewin, Kl, Thara
• Format: Conference Proceeding
• Language: English
• Subjects: Crops; Economics; Image Processing; Internet of Things; Land vehicles; Machine learning; Manuals; Productivity; Robotic Arm; Spraying; Unmanned Ground Vehicle
• ISSN: 2768-0673
• DOI: 10.1109/I-SMAC58438.2023.10290653

India's agriculture sector has contributed greatly to the country's economic expansion. Therefore, reducing expenses and raising crop productivity are essential. In a country like India, where there are hundreds of fields, weeds are always growing there. Weeds and crops fight for space, water, food, nutrients, and other resources, which reduces agricultural output. Currently, one of agriculture's most difficult duties is weed control. Herbicide hand spraying is one of the most popular weed management techniques. However, this strategy has a number of shortcomings. Because manual labor is costly, an automated weed management system may be economically viable. There is currently no technology available that can be utilized in the field in real time to autonomously control in-row weeds, despite repeated attempts. Weed control has become more important as food grain production has increased per person. The suggested system makes an effort to provide a robotic, computer vision-based Unmanned Ground Vehicle (UGV) for real-time weed management in row crops in order to address the aforementioned issues. This tool can recognize weeds and remove them gently without endangering the environment. It would be ideal to achieve crop contact without the involvement of humans using IoT, machine learning, and picture analysis.