Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{151698,
        author = {Naman Mishra and Chandni Agrawal and Piyush Kumar and Vijay Sehrawat and Tara Chand Verma},
        title = {Krishi: A Price Prediction System},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {1},
        pages = {580-583},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=151698},
        abstract = {In today’s world where price prediction systems have become an essential need and are implemented in almost all sectors including estimation of transportation costs or real estate fares, for a country where a major area of land is being used for cultivation this paper tries to understand the importance of price prediction in this field and by overcoming the obstacles and hurdles, find a suitable solution by using the technologies and researches done till date to provide a farmer-friendly solution. This work was done keeping in mind the new Indian Agriculture Acts of 2020 as the middlemen or “Arhatis” (in Hindi) were not just a product link between farmer and customers but also the economic link and were often the ones that decided the prices of crops. With their absence an efficient system is required that can predict the prices for farmers and help them decide accordingly their future ventures.},
        keywords = {Arhati, Crop, Farmer, Machine Learning, MSP, SARIMA, Weather},
        month = {},
        }