An IoT Based Smart Farming System Using Machine Learning
Amine Dahane, Rabaie Benameur, Bouabdellah Kechar, Abou El Hassan Benyamina
Abstract
Smart farming allows to analyze the growth of plants and to influence the parameters of our system in real time in order to optimize plant growth and support the farmer in his activity. Internet of Things (IoT) arrangements, based on the application particular sensors data measurements and intelligent processing, are bridging the holes between the cyber and physical worlds. In this paper, we propose the design and the experiment of a smart farming system based on an intelligent platform which enables prediction capabilities using artificial intelligence (AI) techniques. This system is based on the technology of wireless sensor networks and its implementation requires three main phases, i) data collection phase using sensors deployed in an agricultural field, ii) data cleaning and storage phase, and iii) predictive processing using some AI methods.