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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 114
Article Submitted : 18914
Article Published : 7922
Total Authors : 20931
Total Reviewer : 760
Total Countries : 143
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| Paper Title: | Soil Analysis and Crop Recommendation using Machine Learning |
| Authors Name: | Venugopal M Bhat , G. Tarun Kumar , Shaikh Saifulla , Sharathkumar B S , Dr. Sunitha K |
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| Author Reg. ID: |
IJRTI_188893
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| Published Paper Id: | IJRTI2401039 |
| Published In: | Volume 9 Issue 1, January-2024 |
| DOI: | |
| Abstract: | India constitutes a part of the top three producers of several different crops worldwide and serves as a well-known agricultural center. While Indian farmers play a crucial role in the agriculture industry, a large proportion of them are still at the lower end of the socioeconomic scale. Even with a few technological fixes, farmers still struggle to recognize the most lucrative and viable crops for their soil given the diversity of soil types in different parts of the world. This investigation introduces a crop recommendation system that forecasts the best crop derived from a thorough examination of several criteria, such as geography, soil type, yield, selling price, and more. It does this by using both a Convolutional Neural Network (CNN) architecture and a Random Forest Model. It is anticipated that the CNN design would provide an accuracy rate of 95.21%, while the Random Forest Algorithm may produce an accuracy rate of 75%. |
| Keywords: | Random Forest, Image classification, Deep learning, Convolutional Neural Network, MobileNet v2. |
| Cite Article: | "Soil Analysis and Crop Recommendation using Machine Learning", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.9, Issue 1, page no.228 - 233, January-2024, Available :http://www.ijrti.org/papers/IJRTI2401039.pdf |
| Downloads: | 000205182 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2401039
Registration ID:188893
Published In: Volume 9 Issue 1, January-2024
DOI (Digital Object Identifier):
Page No: 228 - 233 Country: Bengaluru South, Karnataka, India Research Area: Information Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2401039 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2401039 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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