Crop Recommendation System using Machine Learning

Authors

  • Dhruvi Gosai  Charotar University of Science and Technology, Devang Patel Institute of advance Technology and Research, Changa, Department of Computer Engineering, Ta-Petlad, Anand, Gujarat, India
  • Chintal Raval  Charotar University of Science and Technology, Devang Patel Institute of advance Technology and Research, Changa, Department of Computer Engineering, Ta-Petlad, Anand, Gujarat, India
  • Rikin Nayak  Charotar University of Science and Technology, CHARUSAT Space Research and Technology Center, V T Patel Department of E & C Engineering, CSPIT, Changa, Ta-Petlad, Anand, Gujarat, India
  • Hardik Jayswal  Charotar University of Science and Technology, Devang Patel Institute of advance Technology and Research, Changa, Department of Computer Engineering, Ta-Petlad, Anand, Gujarat, India
  • Axat Patel  Charotar University of Science and Technology, CHARUSAT Space Research and Technology Center, C M Department of Mechanical Engineering, CSPIT, Changa, Ta-Petlad, Anand, Gujarat, India

DOI:

https://doi.org//10.32628/CSEIT2173129

Keywords:

Soil nutrient identification, Crop suggestion, Plant pathology, Nitrogen-Phosphorus-Potassium (NPK), Internet of Things (IoT), Machine Learning (ML), Convolutional Neural Network (CNN), K- Nearest Neighbour (KNN).

Abstract

A vast fraction of the population of India considers agriculture as its primary occupation. The production of crops plays an important role in our country. Bad quality crop production is often due to either excessive use of fertilizer or using not enough fertilizer. The proposed system of IoT and ML is enabled for soil testing using the sensors, is based on measuring and observing soil parameters. This system lowers the probability of soil degradation and helps maintain crop health. Different sensors such as soil temperature, soil moisture, pH, NPK, are used in this system for monitoring temperature, humidity, soil moisture, and soil pH along with NPK nutrients of the soil respectively. The data sensed by these sensors is stored on the microcontroller and analyzed using machine learning algorithms like random forest based on which suggestions for the growth of the suitable crop are made. This project also has a methodology that focuses on using a convolutional neural network as a primary way of identifying if the plant is at risk of a disease or not.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2021-06-30

Issue

Volume 7, Issue 3, May-June-2021

Section

Research Articles

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How to Cite

[1]
Dhruvi Gosai, Chintal Raval, Rikin Nayak, Hardik Jayswal, Axat Patel, " Crop Recommendation System using Machine Learning, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 7, Issue 3, pp.558-569, May-June-2021. Available at doi : https://doi.org/10.32628/CSEIT2173129