Unique Registration Number:
Innovator Name:
Mr. Tejas Tawde
Mr. Kunal Deshmukh
Mr. Lobhas Verekar
Mr. Ajay Reddy
Contact No: +917020281499/9075155483
Contact Email: tejastwade845@gmail.com / kunaldeshmukh5245@gmail.com
Project Objective:
i. To detect the rice disease in early stages. To provide the proper pesticide and disease information.
ii. To provide disease identification without the help of expertise.
iii. To provide 24*7 facilities.
iv. To automate the process of disease identification and alerting the farmer.
v. To help farmers grow their production
Abstract:
Rice/Paddy is the staple crop of India. India has the largest area under rice cultivation that includes the cultivation of brown and white rice. Rice cultivation brings employment and also helps to stabilize the Gross Domestic Product (GDP) by its vast contribution. But the production of rice is hampered by various kinds of rice diseases. One of the main diseases of Paddy is leaf disease. Generally, it is very time consuming and laborious for farmers of remote areas to identify the Paddy leaf diseases due to unavailability of experts. Though experts are available in some areas, disease detection is performed by naked eyes which causes inappropriate recognition sometimes. An automated system can minimize these problems. Hence we came up with a model that aims to detect rice plant disease using CNN classifier. The model consists of various sensors like surface temperature recorder, soil moisture recorder, camera sensors which will monitor the rice plant or its complete life cycle.
Project Outcome/result/findings:
The model that can successfully identify six major rice diseases namely leaf blast, rice brown spots, leaf Smut, tungro, sheath rot, and leaf blight. Accuracy to attend for the same is 97%. Also a user friendly web app is created where the user can upload sample images of infected rice leaf and can get the details about the rice disease with fertilizers for the same.
Innovative Approach:
Earlier manual inception was the only way to identify the rice diseases which are more prone to error. Our model, once installed, monitors rice plants throughout its life cycle. With a built-in camera module and sensors, it records the data which is forwarded to the cloud where the data
is analyzed to check for the presence of any sort of disease. If there is any sort of disease. If there is any disease, the model notifies the farmer and provides a detailed report containing the type of disease, its cause and fertilizers and pesticides for the same will be provided.