Automatic Weed Detection and Removal Using AI

Real-time weed detection and identification in autonomous weeding systems are obtained by combining computer vision and machine learning. In this research study, High-resolution images of the field are taken by cameras, which are then processed with convolutional neural networks (CNNs) to precisely detect various types of vegetation. The proposed system is trained on a large and varied dataset, providing high accuracy under different environmental conditions. Through accurate targeting and eliminating undesirable plants with mechanical claws or targeted sprayers, this method maximizes minimal weed presence while maintaining soil and crop integrity. The process improves sustainable agriculture, lowers operational expenditure, and maximizes overall efficiency.