Published Paper Details:

The major problems that are faced by the cultivators are the diseases effecting on their crops. There is no such an authenticated and globalized technique for the detection and diagnosis of plant diseases. In this paper a Mobile diagnostic system for Chili plant was developed as an example to solve this problem. Here we take Chili plant as an example. Chili is one of the widely used as well as cultivated crop not only in our home garden, but also through out our country. India is one of the major producer of Chili crop among the whole world. With the rapid development of mobile service computing, it have an increasingly important role in our daily lives. Disease detection can be more user friendly when we utilize the mobile service computing technique for this purpose. So here we build an image dataset of 4 kinds of Chili diseases along with healthy leaves and healthy fruits. They are collected from the home garden. Then realize a Mobile diagnostic system for Chili diseases by constructing a Deep convolutional neural network (D CNN). The system realized using an Android app in our Mobile device, with which users can upload images and receive diagnostic results. Here the experimental results shows that the detection accuracy of the chili diseases exceeds 90 % and we can detect and receive diagnostic results in a few minutes using this system.