Journal of Cognitive Human-Computer Interaction

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https://doi.org/10.54216/JCHCI

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Journal of Cognitive Human-Computer Interaction

Volume 3, Issue 2, PP: 21-25, 2022 | Cite this article as | XML | | Html PDF

Survey on Crop Recommendation System

Ritika Adhav   1 , AghilaUnnikrishnan   2 , VaishnaviDhumal   3 , SakshiKarade   4 , K.Vengatesan   5 *

  • 1 Computer Engineering, Sanjivani College of Engineering, Kopargoan, Savitribai Phule Pune University, India. - (rittikkaadhav@gmail.com)
  • 2 Computer Engineering, Sanjivani College of Engineering, Kopargoan, Savitribai Phule Pune University, India. - (akhilaaynikkadan@gmail.com)
  • 3 Computer Engineering, Sanjivani College of Engineering, Kopargoan, Savitribai Phule Pune University, India - (dhunalvaishnavi05@gmail.com)
  • 4 Computer Engineering, Sanjivani College of Engineering, Kopargoan, Savitribai Phule Pune University, India - (sakshi.karade16@gmail.com)
  • 5 Computer Engineering, Sanjivani College of Engineering, Kopargoan, Savitribai Phule Pune University, India. - (Vengicse2005@gmail.com)
  • Doi: https://doi.org/10.54216/JCHCI.030203

    Received: January 26, 2022 Accepted: May 29, 2022
    Abstract

    The main purpose of the planned system is to develop a system which can intelligently recommend crop and suggest required measures to farmers for their profitable income. For this purpose, machine learning algorithms are used. The main goal of these systems is to achieve maximum yield rate of crop using land resource. In this system, the farmer / beginner will classify and predict the crop cultivation based on their weather, monsoon and soil type along with their pH level. Forclassification we have used the K-Means algorithm for the choosing crop, the cultivation process is recommended in the form of text. During the cultivation of crops, the fertilizers, insecticides and fungicides are recommended using Machine Learning Technique. The system also predicts the name of disease and its remedies if leaf of crop is diseased .Finally, using this system the farmers will have a well guided approach to begin with farming.The pandemic has affected a lot of fields around the world. One of them is the agricultural sector. Many farmers in the urban as well as the rural parts of India were not able to earn their profile in spite of having good production. This system would eliminate these worries. All the information needed can be accessed online.

    Keywords :

    Machine learning , Deep learning , crop recommendation , fertilizer recommendation , plant disease , Naï , ve Bayes , image processing , classification , K-means.

    References

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    Cite This Article As :
    Ritika Adhav, AghilaUnnikrishnan, VaishnaviDhumal, SakshiKarade, K.Vengatesan. "Survey on Crop Recommendation System." Full Length Article, Vol. 3, No. 2, 2022 ,PP. 21-25 (Doi   :  https://doi.org/10.54216/JCHCI.030203)
    Ritika Adhav, AghilaUnnikrishnan, VaishnaviDhumal, SakshiKarade, K.Vengatesan. (2022). Survey on Crop Recommendation System. Journal of , 3 ( 2 ), 21-25 (Doi   :  https://doi.org/10.54216/JCHCI.030203)
    Ritika Adhav, AghilaUnnikrishnan, VaishnaviDhumal, SakshiKarade, K.Vengatesan. "Survey on Crop Recommendation System." Journal of , 3 no. 2 (2022): 21-25 (Doi   :  https://doi.org/10.54216/JCHCI.030203)
    Ritika Adhav, AghilaUnnikrishnan, VaishnaviDhumal, SakshiKarade, K.Vengatesan. (2022). Survey on Crop Recommendation System. Journal of , 3 ( 2 ), 21-25 (Doi   :  https://doi.org/10.54216/JCHCI.030203)
    Ritika Adhav, AghilaUnnikrishnan, VaishnaviDhumal, SakshiKarade, K.Vengatesan. Survey on Crop Recommendation System. Journal of , (2022); 3 ( 2 ): 21-25 (Doi   :  https://doi.org/10.54216/JCHCI.030203)
    Ritika Adhav, AghilaUnnikrishnan, VaishnaviDhumal, SakshiKarade, K.Vengatesan, Survey on Crop Recommendation System, Journal of , Vol. 3 , No. 2 , (2022) : 21-25 (Doi   :  https://doi.org/10.54216/JCHCI.030203)