Agri Sight: AI-Powered Crop Selection and Product Recommendation System

Authors

DOI:

https://doi.org/10.67308/irjist.073

Keywords:

Smart Agriculture, Crop Prediction, Product Recommendation, Government Schemes, Market Rates;, Web Application

Abstract

Agriculture is important to many economies around the world. Farmers face many challenges, including selecting suitable crops, accessing product information, understanding government programs, and dealing with uncertainty caused by price fluctuations and climate change. Traditional farmers and new agricultural enthusiasts alike may have difficulty making informed decisions because they do not have timely access to reliable resources. The aim of this research article is to develop a centralized, internet-based resource for farmers that provides crop prediction, product recommendations, government subsidy information, and real-time market rates by incorporating user input data, such as location, soil type, and season. The system recommends suitable crop choices and agricultural products based on the user's input data. By integrating emerging technologies into agriculture, including considerations related to climate change, the proposed smart website is intended to help farmers increase productivity, minimize risks, and maximize profits while providing an easy-to-use approach for accessing up-to-date agricultural information through the Internet.

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References

[1] Government of India, Ministry of Agriculture and Farmers Welfare, “Official Agriculture Portal, India.”

[2] Food and Agriculture Organization of the United Nations (FAO), “Digital Agriculture and Smart Farming Concepts.”

[3] S. R. Rajeswari and K. Aravind, “Machine Learning Techniques for Crop Recommendation Systems,” International Journal of Agricultural Technology.

[4] J. Han, M. Kamber, and J. Pei, Data Mining: Concepts and Techniques, Morgan Kaufmann Publishers.

[5] “Crop Recommendation Systems Using Machine Learning,” IEEE Xplore Digital Library.

[6] “Explainable Artificial Intelligence (XAI) in Agriculture,” Springer and Elsevier Publications.

[7] D. P. Ulemale and R. A. More, “Agrarian Crisis and Farmer Suicides in India: A Regional Analysis of Vidarbha,” International Research Journal of Innovation in Science and Technology (IRJIST), vol. 1, no. 1, 2026, DOI: https://doi.org/10.67308/irjist.4

[8] A. A. More and R. A. More, “Agriculture on Wheels: A BioE3 Vision for Green, Sustainable and Resilient Cities,” International Research Journal of Innovation in Science and Technology (IRJIST), vol. 1, no. 3, 2026, DOI: https://doi.org/10.67308/irjist.008

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Published

01-10-2026

How to Cite

Agri Sight: AI-Powered Crop Selection and Product Recommendation System. (2026). International Research Journal of Innovation in Science and Technology, 1(4), 25-28. https://doi.org/10.67308/irjist.073

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