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© 2026 IJSREM – International Journal of Scientific Research in Engineering and Management. This is an open-access journal. Articles are published under the Creative Commons Attribution (CC BY 4.0) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM29821

IoT and Machine Learning Based Crop Suggestion System

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM29821

Volume:

8 |

3 |

Mar 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM29821

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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APSBM

Asst Prof Spoorthi B M

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Abstract

The practise of analysing and extracting meaningful information from enormous amounts of data is referred to as data mining. Data mining is used in a wide range of industries, including banking, retail, medicine, agriculture, and so on. In agriculture, data mining is utilised to investigate the various biotic and abiotic factors that influence crops. Agriculture is India’s most important industry, providing the majority of work possibilities. One of the most common issues that Indian farmers confront is choosing the right crop for their soil. As a result, they are experiencing a major drop in output. Precision agriculture has provided farmers with a solution to this problem. Agriculture with pinpoint accuracy Precision agriculture is a modern agricultural strategy that uses research data on soil features, soil types, and crop yield data to recommend the best crop to produce based on site-specific parameters to farmers. Precision agriculture is gaining popularity.

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Cite This Article

Asst Prof Spoorthi B M, "IoT and Machine Learning Based Crop Suggestion System," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 3, Mar 2024. https://doi.org/10.55041/IJSREM29821

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12/31/45380

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