A survey on different technologies for disease and pest detection in precision agriculture

The development of a nation is mainly based on farming. Bread is the most important nourishment for human well- being. It established that plants being the start of sustenance, significantly experienced few infections. It would hit us strongly if we did not properly care for plants. In this paper, innovation thrives entirely. Nonetheless, it is not possible to farmers to use the expert's service recommendation because of monetary regulations and additional information and difficulties in travelling for treatment. To inform the farmers about the plant's diseases from the expert is tedious. The fastest and most accurate identification of plant diseases will help the farmers from losing yield. The Deep Learning method is the best because it does not need people interaction, even as capturing images, function extraction etc. It has more benefits over different methods like Machine Learning algorithms that could solve properly established troubles. But for more fantastic, more excellent complicated facts packages, we need Deeper Architectures and as. As a result, the new technique includes using a Convolutional Neural Network to discover and analyse plant illnesses like Black measles, Scab, Early blight, Leaf scorch and Bacterial spot.