FarmTrack – A Smart Way of Farming

Authors

  • Ankita Ashok Dhamale  Department of Computer Engineering, ZCOER, Pune, Maharashtra, India
  • Anupriya Vijay Dongare  Department of Computer Engineering, ZCOER, Pune, Maharashtra, India
  • Shubham Rohidas Hundare  Department of Computer Engineering, ZCOER, Pune, Maharashtra, India
  • Prof. Dipali M. Mane  Assistant Professor, Department of Computer Engineering, ZCOER, Pune, Maharashtra, India

Keywords:

Application Programming Interface (API),Crop Prediction, Farming, Management, K-Nearest Neighbor (KNN), Decision Tree, Naïve Bayes, Random Forest, Weather Prediction.

Abstract

Many growing countries are having agriculture as their primary source of revenue. A continuously developing technique for agricultural advances and farming techniques is the modern agriculture. It turns out to be difficult for the farmers to meet our planet’s evolving necessities and the expectancies of merchants, customers, etc. Here, we aim to discover the best model for crop prediction, which can help farmers decide the variety of crop to be grown based on the climatic conditions and nutrients present in the soil. This paper compares popular classifier models such as K-Nearest Neighbor (KNN), Decision Tree, Naive Baiyes and Random Forest using two different criterions, Gini and entropy. Results reveal that Random Forest model gives the highest accuracy amongst them. Alongside to this, we have made a web application which gives us the live weather prediction, and also manages the farmers data securely.

References

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

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Published

2022-04-30

Issue

Volume 8, Issue 2, March-April-2022

Section

Research Articles

License

Copyright (c) IJSRCSEIT

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Ankita Ashok Dhamale, Anupriya Vijay Dongare, Shubham Rohidas Hundare, Prof. Dipali M. Mane, " FarmTrack – A Smart Way of Farming" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 8, Issue 2, pp.479-483, March-April-2022.