Cloud Computing Based Advance System For Detection Of Plant Health

Abstract

It is common for farmers to detect infections by speaking with regional specialists and conducting further experiments. Farming
illnesses that eventually kill crops can impede crop growth. Due to the widespread spread of new diseases, farmers can have trouble
understanding what's happening when things stabilize. In addition to affecting the nation's economy, agricultural diseases are
crucial to controlling. Agricultural losses in India are 22.13% annually. Machine learning and the cloud can be used to identify
diseases automatically to halt further crop losses. Even though a machine learning model is available for this proposal, it is not
particularly advanced, reliable, portable, or practical in many ways. The user interface of the website allows farmers to upload a
photo of a leaf to a cloud-hosted website to see how the disease has affected their crops. With the help of real-time data generated
from 7,000 leaf photos, Convolutional Neural Networks (CNN), MobileNet, and machine learning libraries such as TensorFlow
and OpenCV, it is possible to identify plant diseases with an average accuracy of 98.12%.