TOMATO CARE: A Deep Learning Approach to Disease Recognition and Prevention

Tomatoes are one of the most widely cultivated crops worldwide, but they are often affected by diseases that, if not detected early, can cause significant crop losses. Farmers usually inspect plants manually, which takes time and often results in late detection. To solve this issue, the proposed system offers a smart and practical approach to disease recognition and prevention. It works in three steps: First, it checks environmental conditions like soil moisture to predict the risk of disease early. Second, farmers can upload an image of the affected plant, and the system will detect the disease, assess how severe it is, and suggest treatment. Finally, it shows useful visual insights from past data to help farmers plan better. proposed system helps farmers act quickly, manage diseases more accurately, and grow tomatoes more sustainably.