PLANTAE: An IoT-Based Predictive Platform for Precision Agriculture

Abstract

This paper presents an Internet of Things (IoT) predictive platform for precision agriculture. The proposed platform aims to improve the productivity of crops through auto-controlling the plantation environment at low cost. Furthermore, the platform uses machine learning to predict plant diseases by implementing deep learning algorithms that extract hidden knowledge from the leaves' images to produce a model to achieve the highest possible accuracy of diseases classification. The platform consists of three layers. The first layer collects the needed information and applies the required actions. The second layer provides connectivity to the Internet. The last layer stores data, analyzes it, and makes it accessible to authorized users.