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@article{175163,
        author = {Shruti Tripathi and Anukriti Tonk and Shambhavi Shukla and Priyanshu Goel},
        title = {Agro Advisor for farmers using ML},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {1930-1936},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=175163},
        abstract = {This study introduces Agro Advisor, a web-based platform aimed at assisting farmers by utilizing machine learning (ML) for predictive insights and real-time data access. Farmers frequently encounter difficulties due to a lack of timely information on crop selection, weather updates, government programs, and market rates. To address this, Agro Advisor features a crop prediction model that recommends the most suitable crops based on user-provided environmental conditions. Additionally, the platform delivers updated details on minimum support prices and daily mandi rates. A dedicated weather module is also integrated, allowing farmers to check forecasts for specific locations.},
        keywords = {Crop prediction model, Machine Learning, Weather forecast, Government Schemes, Minimum Support Price, Daily Mandi Price.},
        month = {April},
        }