E-Irrigation Solutions for Forecasting Soil Moisture and Real-Time Automation of Plants Watering

This study deals with the development of e-irrigation solution for forecasting soil conditions and real-time automation of watering in smart agriculture applications. There are several factors that affect agriculture, including limitation of water resources, proper usage of pesticides, inaccuracy in the prediction of soil moisture, inefficient irrigation management, etc. Moreover, traditional irrigation procedures lack proper managing of plants/crops watering that causes wastage of water. As smart farming is an emerging concept, this research work aims of using evolving technologies, such as the "Internet of Things (IoT)", "Information and Communication Technology (ICT)", wireless sensor networks, cloud computing, machine learning, big data, etc. This paper presents a smart irrigation system for predicting irrigation requirements and performing automatic watering process with the help of IoT tools, ICT protocols, and machine learning approaches. The e-irrigation system is developed based on an intelligent irrigation algorithm considering sensors and weather forecasting data. The e-irrigation solution has been implemented in small scale that can predict the soil condition and irrigate plants effectively without human intervention.