Tomato Leaf Disease Detection Using Machine Learning

Leaf diseases are a major danger to the world's food security and have a substantial impact on crop productivity. Effective plant disease management depends on the early identification and precise diagnosis of these illnesses. Recent developments in computer vision techniques and the accessibility of inexpensive hardware, such the Raspberry Pi, have created new avenues for the development of portable and reasonably priced leaf disease detection devices. An innovative Raspberry Pi method for leaf disease detection is shown in this abstract. The proposed approach automatically detects and classifies various leaf diseases using machine learning and image processing techniques. For on-site disease detection in agricultural settings, the Raspberry Pi platform is a perfect fit because of its small size, low power consumption, and computational capacity.