Skip to main content

AI-Powered Fair Trade Platform for Agricultural Market Efficiency

T.P.Udhayasankarm.E

G.Gowrimanogari, T.Shampraison, S.Santhosh, K.Karthik

Abstract

Due to the existence of middlemen, shifting market conditions, and a dearth of real-time knowledge, farmers frequently suffer with unjust pricing and demand forecasting. Due to the inefficiency of the current agricultural supply chain, farmers suffer financial losses and consumers pay higher costs. Fair trade is further hampered by deceptive pricing tactics and a lack of clear verification procedures. In order to eliminate middlemen and guarantee transparent pricing, this paper introduces a fair trade platform driven by artificial intelligence that allows farmers to sell their produce directly to buyers and sellers. In order to help farmers make well-informed decisions about crop production and pricing, the system uses Machine Learning (ML) to forecast demand based on historical data, market trends, and climatic conditions. An AI-driven price verification mechanism ensures that the selling price aligns with real-time market rates, preventing fraudulent pricing and exploitation.

Article Information

Journal

International Journal of Science, Research and Technology

Volume (Issue)

Vol. 8 No. 2 (2025): International Journal of Science, Research and Technology (IJSRAT)

DOI

https://doi.org/10.15662/IJSRAT.2025.0802009

Pages

13904-13912

Published

April 15, 2025
Copyright

Open Access

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

T.P.Udhayasankarm.E, G.Gowrimanogari, T.Shampraison, S.Santhosh, K.Karthik (%2025). AI-Powered Fair Trade Platform for Agricultural Market Efficiency. International Journal of Science, Research and Technology , Vol. 8 No. 2 (2025): International Journal of Science, Research and Technology (IJSRAT) , pp. 13904-13912. https://doi.org/10.15662/IJSRAT.2025.0802009

References

1. S. Mittal and M. Kumar, "Prediction of Price in Agricultural Commodity Using Machine Learning," 2019 10th International Conference on Computing, Communication and Networking Technologies (ICCCNT), Kanpur, India, 2019, pp. 1-7.
2. M.A.Khan, M.U.Akram and M. Khan, "A Machine Learning Approach for Price Prediction in the Agricultural Commodity Market," 2018 International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), Sukkur, Pakistan, 2018, pp. 1-5.
3. Y.Liu,X.Chen,andY.Wang,"A Price Forecasting Model for Agricultural Products Based on Long Short-Term Memory Neural Network," 2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD), Guilin, China, 2017, pp. 1357-1361.
4. K. Sahu and S. P. Singh, "An Approach for Prediction of Agricultural Commodities Using Fuzzy Time Series," 2016 International Conference on Computing, Communication and Automation(ICCCA),Noida,India, 2016,pp.1018-1021.
5. S. S. Patil and S. S. Patil, "A Study on Agricultural Price Prediction Using Machine Learning and Big Data," 2016 International Conference on Computing Communication Control andAutomation(ICCUBEA),Pune,India,2016, pp.1-6.