AI in Agriculture: Advanced Smart Irrigation for Enhanced Crop Yields

Department of CS & IT, Kalinga University, Raipur, India, and Dhablia Dharmesh Kirit, Research Scholar, Department of CS & IT, Kalinga University, Raipur, India

^* Corresponding author: ku.frahman@kalingauniversity.ac.in

Abstract

Integrating Artificial Intelligence (AI) into the process of agriculture is changing the way this business is taking place. The work presented here concentrates on designing and realizing an advanced AI driven smart irrigation system for tackling the main issues like water scarcity and inefficient irrigation practices that diminish crop productivity and waste resources. The proposed smart irrigation system will leverage machine learning algorithms, predictive analytics, as well as other AI technologies and real time data in the soil moisture, weather conditions, crop health and water usage. It will use predictive models and ensure that exact, timely irrigation is used, hemmed in to specific crop need requirements in order to minimize wasted water and increase water use efficiency for optimum crop growth. The evaluations of the system effectiveness are by simulations and field trial as part of the research. Water consumption, crop yield, and resource utilization efficiency will be analyzed to the utmost degree. The expected outcomes are that a significant reduction in water usage will be realized, development of best practices for smart irrigation in agriculture, and increased crop yields. The purpose of this study is to modernize existing irrigation practices in order to secure food and sustainable agriculture. The findings offer great insights and provide a generalisable framework to deploy the AI based smart irrigation systems to bring benefits to the farmers, policymakers and other stakeholders in the agricultural domain.