<![CDATA[Soil quality plays a crucial role in determining agricultural productivity, making accurate and continuous monitoring essential. This study focused on designing and developing a soil fertility monitoring system that delivers real-time information and predicts crop suitability. The system integrates sensor-based data collection with intelligent data processing techniques. Soil data were obtained using a multi-parameter sensor and then processed through stages of cleaning, normalization, and feature preparation. Multiple algorithms were trained to detect patterns in soil conditions and enhance prediction capabilities. The system architecture comprises data acquisition, transmission, storage, and visualization to support effective monitoring. A systematic development approach was employed, including preparation, implementation, and integration phases. The proposed system facilitates efficient soil data management and promotes precision agriculture through ongoing monitoring and predictive analysis of soil conditions.]]>
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