AIoT-Based Data-Driven Irrigation and Fertilization Smart System

Abstract

Agriculture is a prime industry and the foundation of a country's economy. Thus, advancement and automation in the agriculture industry is the foremost objective of any growing country. Initially, the farmers were using manual methods to regulate irrigation and fertilizers. Manual irrigation and fertilization is also a major reason for the huge loss of productivity. The irregularity of these two is the reason for major problems in an agricultural crop. The addressed issues can be resolved with some automated methods based on artificial intelligence. The proper implementation of improvements in irrigation and fertilization is crucial for the efficient utilization of these resources and also contributes to Sustainable Development Goals (SDGs). Consequently, a data-driven smart farming system has been proposed to resolve issues related to irrigation and fertilization. Here a hybrid deep learning technique has been employed in the system to provide prediction data.