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PreprintCC BY 4.0Zenodo

Integrated Farmer Advisory and Marketplace System Using Machine Learning

  • Disha D S1
  • Disha H Jain1
  • Dhruhi Atykar1
  • Parth Rawat1
  • Vanishree K
  1. 1B.M.S. College of Engineering
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Abstract

This paper presents an Integrated Farmer Advisory and Marketplace System Using Machine Learning, designed to support farmers in making informed agricultural decisions. The system integrates crop recommendation using the Random Forest algorithm, agricultural price prediction using XGBoost, expert consultation through image and description uploads, and guidance on government-recommended agricultural inputs. It also provides a digital marketplace that enables transparent interaction between farmers and buyers through a bidding mechanism. By combining crop selection, input guidance, expert assistance, price forecasting, and market access within a unified platform, the proposed system aims to help farmers make better cultivation and selling decisions, reduce unnecessary expenses, and improve access to agricultural information and market opportunities.

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Cite

BibTeXRIS
BibTeX
@misc{d2026integrated,
  title = {{Integrated Farmer Advisory and Marketplace System Using Machine Learning}},
  author = {Disha D S and Disha H Jain and Dhruhi Atykar and Parth Rawat and Vanishree K},
  howpublished = {Zenodo},
  year = {2026},
  month = oct,
  doi = {10.5281/zenodo.23543133},
  url = {https://zenodo.org/records/23543133},
  note = {CC BY 4.0},
}
RIS
TY  - UNPB
TI  - Integrated Farmer Advisory and Marketplace System Using Machine Learning
AU  - Disha D S
AU  - Disha H Jain
AU  - Dhruhi Atykar
AU  - Parth Rawat
AU  - Vanishree K
PY  - 2026
DA  - 2026/10/21
PB  - Zenodo
DO  - 10.5281/zenodo.23543133
UR  - https://zenodo.org/records/23543133
AB  - This paper presents an Integrated Farmer Advisory and Marketplace System Using Machine Learning, designed to support farmers in making informed agricultural decisions. The system integrates crop recommendation using the Random Forest algorithm, agricultural price prediction using XGBoost, expert consultation through image and description uploads, and guidance on government-recommended agricultural inputs. It also provides a digital marketplace that enables transparent interaction between farmers and buyers through a bidding mechanism. By combining crop selection, input guidance, expert assistance, price forecasting, and market access within a unified platform, the proposed system aims to help farmers make better cultivation and selling decisions, reduce unnecessary expenses, and improve access to agricultural information and market opportunities.
ER  -