Machine Learning Approaches for Soil Quality Classification in Precision Agriculture
DOI:
https://doi.org/10.48047/vtw21b75Keywords:
Keywords: Soil type classification, Precision agriculture, Predictive analytics, Machine Learning, Deep CNN.Abstract
maximizing productivity. Traditional manual methods, which involve physical sample collection, laboratory analysis, and expert interpretation, are time-consuming, costly, and prone to human error— leading to delays and inconsistent outcomes in decision-making. To address these challenges, this research aims to automate soil classification using advanced artificial intelligence techniques, integrating classical machine learning models with deep learning approaches in a unified, user-friendly system
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