An Intelligent IOT and AI-Based Smart Farming Framework for Real-Time Crop Monitoring, Predictive Analytics, and Sustainable Agriculture

Abstract

ABSTRACT Agriculture remains the backbone of many economies worldwide, yet farmers continue to face challenges related to climate variability, water scarcity, soil degradation, pest infestations, and inefficient resource utilization. Traditional farming methods often rely on manual observation and experience-based decision-making, which may lead to reduced productivity and increased operational costs. The integration of the Internet of Things (IoT) and Artificial Intelligence (AI) has emerged as a transformative solution for modern agriculture by enabling real-time monitoring, intelligent data analysis, and automated decision-making. This paper proposes a Smart Farming System that combines IoT sensors, wireless communication technologies, cloud computing, and AI-based predictive models to optimize agricultural practices. The proposed framework continuously monitors environmental conditions such as soil moisture, temperature, humidity, light intensity, and crop health. AI algorithms analyze the collected data to predict irrigation requirements, detect diseases, estimate crop yield, and recommend suitable farming actions. The system aims to improve agricultural productivity, reduce resource wastage, and promote sustainable farming practices. Experimental results demonstrate significant improvements in water efficiency, crop yield prediction accuracy, and overall farm management performance. The proposed solution provides a scalable and cost-effective approach toward the development of intelligent agriculture systems capable of meeting future food security demands. Keywords— Smart Farming, Internet of Things (IoT), Artificial Intelligence (AI), Precision Agriculture, Crop Monitoring, Machine Learning, Sustainable Agriculture, Smart Irrigation.