(untitled) (Journal of Pharmaceutical Negative Results, 2023)
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%.