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Integrated ML-driven agricultural Technology Platform for Personalized Recommendations for Crop Selection, Resource Management, and Market Participation

  • Unique Paper ID: 164583
  • Volume: 10
  • Issue: 12
  • PageNo: 1866-1873
  • Abstract:
  • India's agricultural sector, a significant contributor to the nation's GDP and workforce, faces challenges due to traditional farming practices and reliance on weather patterns. This research proposes a data-driven approach to empower farmers with optimal crop selection. By analyzing environmental factors such as soil nutrient levels, pH, humidity, and rainfall patterns, machine learning models including Decision Trees, Support Vector Machines, Logistic Regression, and Gaussian Naive Bayes will be applied to develop a website with a robust crop recommendation system. This system aims to bridge the gap between tradition and modernity, enhancing agricultural efficiency and productivity for Indian farmers.
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Cite This Article

  • ISSN: 2349-6002
  • Volume: 10
  • Issue: 12
  • PageNo: 1866-1873

Integrated ML-driven agricultural Technology Platform for Personalized Recommendations for Crop Selection, Resource Management, and Market Participation

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Journal no 47859

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