Certain investigation on intelligent irrigation systems using machine learning for uncertain conditions

Abstract

Agriculture is the backbone of the Indian economy and technology newlinerevolutionizes traditional farming to increase productivity while utilizing newlineresources without wastage. Incorporation of technology in traditional newlineagriculture lands in modern agriculture, where most of the processes are newlineautomated. The process of agricultural activity automation brings ineffective newlinemanagement, increased yield, continuous monitoring, and so on. newlineThough numerous issues can be automated in agriculture, newlineirrigation management is the most crucial issue to be addressed, as it plays a newlinekey role in crop cultivation. Water scarcity is the biggest problem in the world newlinethat mainly affects the agriculture system. Irrigation systems come in a newlinevariety of configurations. A basic irrigation system is insufficient to perform newlineagriculture on a large piece of land. Hence, the technology is deployed in a newlinedifferent way to increase crop yield. newlineThe advantages of an automated irrigation system are minimized newlinewater wastage, ease of execution, minimal labor, and so on. Understanding newlinethe seriousness of this issue, this research work presents three effective newlinesolutions for an automatic irrigation system for agriculture. The first phase of newlinethis work utilizes the concept of the multiplex barrel framework to handle a newlinelarge amount of data in each layer of big data. This work yields a high-quality newlinecrop with a sufficient water supply. newlineThe second phase of the work utilizes Generalized Regression newlineNeural Networks (GRNN). newline