GreenAssist: an IoT-powered Multi-Field Irrigation and Fertilizer Management System for Enhancing Agricultural Productivity

Agriculture plays a vital role in a country's economy, yet farmers struggle with challenges such as land scarcity, population growth, inefficient resource management, and the impacts of climate change. To address these challenges, this research proposed an intelligent system to enhance agricultural productivity through automated irrigation and fertilizer recommendations. The proposed system ensures efficient water use and supports sustainable farming practices by monitoring soil moisture and integrating real-time weather forecasts. Besides this research ensures to use the rainwater, which will be beneficial as it will ensure lower power consumption. The three machine learning algorithms were explored to recommend fertilizers to specific crops based on soil nutrition. The evaluation study showed that the system achieved high accuracy (99.67%) in predicting methods needed for crop-specific fertilizer and effectively maintained ideal soil moisture levels for different crops, reducing water waste, using rainwater, and optimizing nutrient management. As such, the system will contribute to improving agricultural efficiency and to the economic development of rural areas in developing countries.