Abstract:
We know that the root of the potato tree is used as a food in many countries of the world. It
is called potato. Scientific name is “Solanum Tuberosum”. It is from the Solanaceae family.
The Solanaceae family prefers cool weather to grow. The best is between 15 to 18 degrees
and required PH for soil is 5.5 to 6.0. More temperature can make an effect for growing in
tropical Africa, potatoes are cultivated in high lands about 1500 to 3500 meters above sea
level. The year “2008” was celebrated as “international potato year” which was organized by
a United States organization dated 18th October, 2007. The sector of agriculture has been now
a key backbone to Bangladesh’s economy. Bangladesh has a large population who take potato
as a side meal with “Rice”. As potato cultivation is huge it has several diseases. The most
common is late blight and early blight. It is quite tough to detect potato’s disease from
sightseeing. That's why we used different kinds of sensors for detecting those diseases.
Detecting those diseases through AI we can find an easy solution. And also it will help our
farmer to take necessary steps in time. And they will be able to grow as their target. To grow
healthy crops, we need to find out the problem, to maintain the health of the food. And by
using technology now it is very simple. Here we decided to use convolutional neural networks.
It is a class of deep neural networks, in deep learning, which is applied commonly to analyzing
visual imagery. We will use the image of potato leaves to analyze if it is healthy or not.
In this segmentation approach and utilization of support vector machines demonstrate disease
classification over 2152 images with an accuracy level of 98.29%. Thus, our proposed
approach presents a path toward automatic disease diagnosis of plants on a great scale.
