Advancing Food safety through IoT : real time monitoring and control system

Abstract

Diseases in fruit and vegetable cause devastating problem in economic losses and production in agricultural industry worldwide. In this project an adaptive approach for the identification of fruit diseases and vegetable is proposed and experimentally validated. In this project, this approach will be detecting the diseases which affect the fruits and can even identify some types of diseases which attacks fruits based on some comparisons. On account of that, the approach is using CNN(Convolutional Neural Networks), which is a deep learning algorithm that is where input is taken as images, and those images were differentiated based on various aspects and parameters taken from it and is most commonly applied to analyzing visual imagery. This will be definitely helpful for the farmers to enhance the growth of the crops in the mere future. For this approach, python language has been chosen for further analysis. By applying this proposed system, the accuracy level reached is 97%.