A Study to Maximize the Agricultural Production and Minimize the use of Fertilizers

Authors

  • Kavya Gupta  Department of Information Technology, Maharaja Agrasen Instute of Technology, GGSIP University, Delhi, India
  • Mrs Nidhi Senger  Faculty, Department of Information Technology, Maharaja Agrasen Instute of Technology, GGSIP University, Delhi, India
  • Mrs. Vasudha Bahl  Faculty, Department of Information Technology, Maharaja Agrasen Instute of Technology, GGSIP University, Delhi, India
  • Dr. Amita Goel  Faculty, Department of Information Technology, Maharaja Agrasen Instute of Technology, GGSIP University, Delhi, India

DOI:

https://doi.org/10.32628/CSEIT217644

Keywords:

Node Deployment, Routing, Artificial Bee Colony, Wireless Sensor Networks.

Abstract

A large number of people have attempted to create mathematical models in order to develop and optimize agricultural production; however almost none of them address the factors such as use of fertilizers (N, K, P). More use of fertilizers can deteriorate the fertility of soil and can lead to the low production for years to come. In this study a predictive model is formulated that aims to predict the best crop to be grown in available weather conditions and nutrients present in the soil thereby reducing the use of chemicals and taking a step forward towards organic and chemical free agriculture.

References

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

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Published

2021-12-30

Issue

Volume 7, Issue 6, November-December-2021

Section

Research Articles

License

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

How to Cite

[1]
Kavya Gupta, Mrs Nidhi Senger, Mrs. Vasudha Bahl, Dr. Amita Goel, " A Study to Maximize the Agricultural Production and Minimize the use of Fertilizers" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 7, Issue 6, pp.225-231, November-December-2021. Available at doi : https://doi.org/10.32628/CSEIT217644