Soil Health Monitoring System using Random Forest Algorithm

Authors

  • Akanksha Mahangare Student, Department of Information Technology, MIT Art, Design & Technology University, Pune, India
  • Jatin Kumar Student, Department of Information Technology, MIT Art, Design & Technology University, Pune, India
  • Rhea Simon Student, Department of Information Technology, MIT Art, Design & Technology University, Pune, India
  • Shubham Mallick Student, Department of Information Technology, MIT Art, Design & Technology University, Pune, India
  • Arvind Jagtap Associate Professor, Department of Information Technology, MIT Art, Design & Technology University, Pune, India
  • Rishikesh Yeolekar Assistant Professor, Department of Information Technology, MIT Art, Design & Technology University, Pune, India

Keywords:

Crop recommendation, IoT, Machine Learning, NPK sensor, Random Forest, Soil health

Abstract

Agriculture is India's largest economic sector and plays a critical role in the country's overall socioeconomic development. Indian farmers produce less than farmers in other countries due to inadequate usage and implementation of modern agricultural practices and technologies and it leads to low productivity, which is impeded by neglect and high expenses. Knowing the level of soil nutrients can help farmers enhance agricultural output because insufficient nutrient levels can affect crop yield, while excess nutrient levels can either have the same effect or be wasted. A machine learning-based remote monitoring system can boost crop productivity and quality. The application of appropriate machine learning algorithms to collect data and analyze it can benefit in crop recommendation.

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Published

18-06-2022

How to Cite

[1]
A. Mahangare, J. Kumar, R. Simon, S. Mallick, A. Jagtap, and R. Yeolekar, “Soil Health Monitoring System using Random Forest Algorithm”, IJRESM, vol. 5, no. 6, pp. 141–143, Jun. 2022.

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Articles