Artificial Intelligence - Driven Autonomous Robot for Crop Cultivation

Abstract

Agriculture has been considered as the primary occupation by more than 42% of the total population in the world. It can also be seen that agriculture is known as the ‘Backbone of India’, since more than 70% of the Indian population depends on agriculture. The main goal of Agribot is to apply technologies related to robotics in the field of agriculture. Weeds are plants that take up space in an unproductive area and compete with other crops mainly for light, nutrients, water, and space. The labor-intensive task of weed control frequently makes agricultural challenges like lower yields and higher hardware demands worse. In addition to posing a resource competition with crops, weeds harbor illnesses that have the potential to significantly reduce agricultural output. Our suggested remedy is to incorporate a camera into the farming apparatus. By making use of the live video feed that this camera will offer, weeds among the crops can be identified using image processing techniques. To differentiate between weeds and crops, the Convolutional Neural Network (CNN) algorithm will be used by the system. Through training, the CNN algorithm will extract pertinent information from photos to improve the accuracy of weed detection, opening the door for an effective and automated weed management system.