Artificial Intelligence-Driven IoT Solutions for Sustainable Soil Management and Crop Yield Optimization
Keywords:
Artificial Intelligence (AI), Internet of Things (IoT), Sustainable Agriculture, Soil Management, Crop Yield Prediction, Machine Learning, Precision Farming.Abstract
The integration of Artificial Intelligence (AI) and the Internet of Things (IoT) has significantly transformed modern agricultural practices by enabling intelligent and data-driven decision-making. This study presents an AI-driven IoT framework for sustainable soil management and crop yield optimization. The proposed system utilizes various soil sensors to monitor critical parameters such as soil moisture, temperature, pH, and nutrient levels in real time. The collected data are transmitted through IoT-enabled devices to a cloud platform, where machine learning algorithms analyze the information and generate recommendations for irrigation, fertilization, and crop management. The system helps farmers improve resource utilization, reduce water and fertilizer wastage, and enhance agricultural productivity. Experimental results indicate that AI-based predictive models can accurately estimate crop yield and support sustainable farming practices. The integration of AI and IoT offers an effective solution for increasing food production while preserving soil health and environmental sustainability.
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