• Vignesh D
• Prajwal Raj T D
• Kushal S
• Shrinidhi M
• Mr. Darshan Halliyavar

In this paper, we propose a technique for detection of the diseases like bacterial leaf blight, brown spot disease and leaf smut in paddy crop using one of the deep learning algorithms called as CNN algorithm. The entire system works on a laptop which acts as processing unit for the proposed system. The well trained Keras model to predict the disease in paddy leaf is developed using CNN algorithm. As the symptoms of the diseases are detected using feature of the paddy leaf, the model is trained using the diseased image data set. The images will be processed by the python script running on the laptop. The trained model will predict the disease using the processed image of the leaf containing the symptoms of the disease. The proposed system also includes the feature which will alert the farmer about spreading of the disease by using the Wi-Fi module to send the message to the farmer of the field through the web application. Also, the pesticides are sprayed by the system to control the further growth of the germs causing the disease. In India paddy is grown as the staple crop. The paddy crop is mostly damaged due to the leaf diseases which are mentioned above. Hence, by implementing this technique, the disease can be detected and loss can be decreased.

Arduino Uno, CNN Algorithm, Bacterial Leaf Blight, Brown Spot Disease, Leaf Smut.

"Disease Detection in Paddy Crop Using CNN Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 5, page no.g33-g38, May-2022, Available :http://www.jetir.org/papers/JETIR2205703.pdf

"Disease Detection in Paddy Crop Using CNN Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 5, page no. ppg33-g38, May-2022, Available at : http://www.jetir.org/papers/JETIR2205703.pdf