Tomato Leaf Disease Detection and Monitoring System

Agriculture plays an important role in Indian economy. Technology helps in increasing the production of food. However, the production of food can be affected by number of factors such as climatic change, diseases, soil fertility etc. Tomato leaf disease has the potential to result in 40 percent of crop loss. Economic loss of about USD 11 billion was estimated to disease detection alone in 10 major crops of India. Tomato leaf disease increases the cost of agriculture and hinders the progress of work and damages crops by affecting their growth. Disease control is an important aspect of crop management, as failure to adequately control disease it leads to reduce yields and product quality. Automatic detection of Tomato leaf disease proves benefits in monitoring large fields of crops. The proposed work consists of modules namely tomato leaf disease detection module to detect the disease and automate the agribot to spray the pesticides, Robot movement module to control the agribot movements based on the presence of leaf disease. Tools and technologies used to implement the proposed work are arduino IDE, python IDLE, Embedded C. Flask is a framework where CNN algorithm is used in it. The outcome of the proposed project is to help the farmers through an agribot which detects the tomato leaf disease in the field by image processing and sprays the pesticides to prevent the damages for crops. It will be very useful to increase the production of food and also reduces the man power.