Precise Management for Smart Farming in Hydroponics based on IoT using Supervised Machine Learning Approach

This paper presents a framework for automated smart farming in hydroponics using Internet of Things. The difficulties to be addressed with this framework are the expanding food interest on the planet, the need for a market of new supportable techniques for cultivating utilizing the Internet of Things. The proposed architecture is characterized into mainly four components, hydroponics farm site, device layer, communication layer, fog layer and finally cloud layer. Data Analytics is deployed at the fog layer for effective computation over the cloud layer and implemented using supervised machine learning algorithms for two different scenarios, precision and intelligence by using regression and classification algorithms respectively. The framework improved its exhibition and permits it to effectively accomplish the point of the whole framework executed