• Veena Krishnan G
• N.Kumareshan

In this paper an automated system has been developed to determine whether the plant’s leaf is healthy or disease affected. The normal growth of the plants, yield and quality of agricultural products is seriously affected by plant diseases. This paper aims to develop a computer vision based automatic system for the diagnosis of diseases in plant leaves. Automatic disease detection using computer vision approach involves the segmentation using k mean clustering and feature extraction of diseased area of the leaf, textural descriptors using gray level co-occurrence matrix (GLCM). Color moments are extracted from diseased and non-diseased leaf images resulting in feature values. CNN and BRNN are used for classification. Classified leaves with diseases result to display on android APP using Bluetooth. And also pesticides are sprayed on the detected unhealthy leaves using centrifugal motor pump.

CNN, BRNN, Arduino, Lcd, Motor, Bluetooth

"Android Based Plant Disease Detection Using Arduino", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.139-142, May-2019, Available :http://www.jetir.org/papers/JETIR1905D18.pdf

"Android Based Plant Disease Detection Using Arduino", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp139-142, May-2019, Available at : http://www.jetir.org/papers/JETIR1905D18.pdf