Location
https://www.kennesaw.edu/ccse/events/computing-showcase/sp26-cday-program.php
Document Type
Event
Start Date
22-4-2026 4:00 PM
Description
The Smart Soil Analyzer is a machine learning-based application designed to maximize agricultural efficiency and sustainability. Our team developed a predictive system using a K-Nearest Neighbors (KNN) classifier trained on a comprehensive crop recommendation dataset. The tool allows users to input key environmental and soil metrics, including Nitrogen (N), Phosphorus (P), Potassium (K), temperature, humidity, pH levels, and rainfall. By processing these variables, the model accurately predicts the most suitable crop for the specific land conditions. This solution provides farmers with data-driven insights to optimize yields, reduce fertilizer waste, and combat soil degradation through precise crop matching.
Included in
UC-162-194 Smart Soil Analyzer
https://www.kennesaw.edu/ccse/events/computing-showcase/sp26-cday-program.php
The Smart Soil Analyzer is a machine learning-based application designed to maximize agricultural efficiency and sustainability. Our team developed a predictive system using a K-Nearest Neighbors (KNN) classifier trained on a comprehensive crop recommendation dataset. The tool allows users to input key environmental and soil metrics, including Nitrogen (N), Phosphorus (P), Potassium (K), temperature, humidity, pH levels, and rainfall. By processing these variables, the model accurately predicts the most suitable crop for the specific land conditions. This solution provides farmers with data-driven insights to optimize yields, reduce fertilizer waste, and combat soil degradation through precise crop matching.