Early detection of grapes diseases using machine learning and IoT

Grape cultivation has social and economic importance in India. In India, Maharashtra ranks first in grapes production. Over the last few years the quality of grapes has degraded because of many reasons. One of the important causes is diseases on grapes. To prevent diseases farmers spray huge amount of pesticides, which result in increasing the cost of production. Also farmers are unable to identify the diseases manually. The diseases are identified only after the infection, but its takes up a lot of time and have adverse effects on vineyard. The proposed work is to develop a monitoring system which will identify the chances of grape diseases in its early stages by using Hidden Markov Model provides alerts via SMS to the farmer and the expert. The system includes temperature, relative humidity, moisture, leaf wetness sensor and Zig-Bee for wireless data transmission.