Machine Learning and Remote Sensing for Soil Moisture and Nutrient Estimation: A Systematic Review and Future Research Roadmap

The need for innovative and effective agricultural practices is now more than higher due to the growing demand for food worldwide and the strain on land and water resources. In order to make farming more data-driven, focused, and sustainable, precision agriculture (PA) provides a potent solution by utilizing technologies such as remote sensing, artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT). This paper discusses the various ways in which precision agriculture is revolutionizing each step of agricultural production, from supply chain optimization and pest and disease detection to soil health evaluation and smart irrigation. Based on current research and practical uses, particularly in India, we demonstrate how technologies like satellite images, unmanned aerial vehicles (UAVs), artificial intelligence (AI)-powered sensors, and automated equipment assist farmers in improving decision-making, cutting waste, conserving resources, and increasing output. Even while PA technologies are becoming increasingly popular, issues including excessive costs, a lack of regulations, and limited availability for smallholder farmers still exist. This study emphasizes how important precision agriculture is to creating a farming system that is more robust, effective, and prepared for the future.