GIS-Enhanced Crop Yield Modeling with Machine Learning
India, with its vast population and agrarian society, faces challenges in agricultural practices. Many farmers continue to grow the same crops repeatedly without experimenting with new varieties. To address these issues, we have developed a system using machine learning algorithms aimed at helpin...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English English |
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INTI International University
2024
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| Subjects: | |
| Online Access: | http://eprints.intimal.edu.my/2082/ http://eprints.intimal.edu.my/2082/2/623 http://eprints.intimal.edu.my/2082/3/joit2024_37b.pdf |
| _version_ | 1848766915105783808 |
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| author | Venkatesh, S.D. Chitra, K. Harilakshami, V.M. |
| author_facet | Venkatesh, S.D. Chitra, K. Harilakshami, V.M. |
| author_sort | Venkatesh, S.D. |
| building | INTI Institutional Repository |
| collection | Online Access |
| description | India, with its vast population and agrarian society, faces challenges in agricultural practices.
Many farmers continue to grow the same crops repeatedly without experimenting with new
varieties. To address these issues, we have developed a system using machine learning
algorithms aimed at helping farmers. Our system recommends the most suitable crops for
specific lands based on soil content and weather conditions. It also provides information on
the appropriate type and number of fertilizers and the necessary seeds for cultivation. By using
our system, farmers can diversify their crops, potentially increase their profit margins, and
reduce soil pollution. |
| first_indexed | 2025-11-14T11:58:43Z |
| format | Article |
| id | intimal-2082 |
| institution | INTI International University |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T11:58:43Z |
| publishDate | 2024 |
| publisher | INTI International University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | intimal-20822025-07-12T03:07:10Z http://eprints.intimal.edu.my/2082/ GIS-Enhanced Crop Yield Modeling with Machine Learning Venkatesh, S.D. Chitra, K. Harilakshami, V.M. QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) India, with its vast population and agrarian society, faces challenges in agricultural practices. Many farmers continue to grow the same crops repeatedly without experimenting with new varieties. To address these issues, we have developed a system using machine learning algorithms aimed at helping farmers. Our system recommends the most suitable crops for specific lands based on soil content and weather conditions. It also provides information on the appropriate type and number of fertilizers and the necessary seeds for cultivation. By using our system, farmers can diversify their crops, potentially increase their profit margins, and reduce soil pollution. INTI International University 2024-12 Article PeerReviewed text en cc_by_4 http://eprints.intimal.edu.my/2082/2/623 text en cc_by_4 http://eprints.intimal.edu.my/2082/3/joit2024_37b.pdf Venkatesh, S.D. and Chitra, K. and Harilakshami, V.M. (2024) GIS-Enhanced Crop Yield Modeling with Machine Learning. Journal of Innovation and Technology, 2024 (37). pp. 1-7. ISSN 2805-5179 http://ipublishing.intimal.edu.my/joint.html |
| spellingShingle | QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) Venkatesh, S.D. Chitra, K. Harilakshami, V.M. GIS-Enhanced Crop Yield Modeling with Machine Learning |
| title | GIS-Enhanced Crop Yield Modeling with Machine Learning |
| title_full | GIS-Enhanced Crop Yield Modeling with Machine Learning |
| title_fullStr | GIS-Enhanced Crop Yield Modeling with Machine Learning |
| title_full_unstemmed | GIS-Enhanced Crop Yield Modeling with Machine Learning |
| title_short | GIS-Enhanced Crop Yield Modeling with Machine Learning |
| title_sort | gis-enhanced crop yield modeling with machine learning |
| topic | QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) |
| url | http://eprints.intimal.edu.my/2082/ http://eprints.intimal.edu.my/2082/ http://eprints.intimal.edu.my/2082/2/623 http://eprints.intimal.edu.my/2082/3/joit2024_37b.pdf |