Plants get exposed to various attacks by microorganisms, disease caused by bacteria and insects. The warnings of the attacks are clearly distinguished through the leaves, stem and fruit inspection, where either one of these are affected. In Recent Years, Deep Learning has led to great performance in various fields like Image Recognition, Speech Recognition, and Natural Language Processing. The use of the Convolution Neural Network in the Problem of Plant Disease Detection has very good results. Early Disease Detection is important for better yield and quality of crops. With Reduction in Quality of the Agricultural Product, Diseased Plant can lead to the huge Economic Losses to the Individual farmers. In this paper we have proposed a Machine learning-based approach for image recognition. Convolution Neural Network comes under the sub domain of Machine Learning. It involves the extraction of features from the image to observe some patterns in the dataset. The model uses RFID module to switch on or off the camera. The RFID module is used to protect the camera from capturing unwanted images which can be used later. The output of the sample leaves images will be displayed in the LCD display. Hardware implementation of this project has been done and the results are compared with simulation results. The simulation is carried out in Tensor Flow to obtain the system performance.