Leaf Disease Detection

Agriculture plays a vital role in the economic development of India, yet crop productivity is significantly affected by plant diseases, inefficient irrigation practices, and excessive dependence on manual labour. Early detection of crop diseases and optimized utilization of water resources remain major challenges for farmers. This paper presents the design and development of an Agribot for automated agriculture that integrates soil moisture sensing, robotic movement, and image-based leaf disease detection. The proposed system continuously monitors soil conditions, automates irrigation based on moisture levels, and detects leaf diseases at early stages using image processing techniques. By reducing human intervention and enabling precision farming, the Agribot enhances crop yield, conserves water, and improves overall agricultural efficiency