Agriculture plays a vital role in the economy, but farmers often face challenges in selecting suitable crops based on soil type, weather conditions, and environmental factors. Manual decision-making can lead to reduced yield and inefficiency. To overcome this problem, this project proposes an Agro AI Assistant, a smart agriculture-based system that utilizes Machine Learning and Computer Vision techniques to support farmers and home gardeners in making better agricultural decisions. The system provides crop recommendations based on soil and climatic conditions and also performs image-based crop identification using a trained deep learning model. Additionally, it offers useful guidance on crop cultivation methods, water-saving techniques, terrace gardening practices, and yield improvement strategies. By integrating AI into agriculture through a user-friendly web application, this project aims to enhance productivity, reduce manual effort, and promote smart farming practices for sustainable agriculture.
Monisha et al. (Wed,) studied this question.