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@article{187088,
        author = {NITHYA R and NARMADHAVARSHINI N and K.Rajeswari},
        title = {AGRIFORECAST A MACHINE LEARNING BASED CROP PRICE PREDICTION AND ADVISORY SYSTEM FOR RURAL FARMERS},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {6},
        pages = {3663-3668},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=187088},
        abstract = {Agriculture is the main source of income for many rural farmers, but they often face problems in predicting crop prices and choosing the right crops to grow. AgriForecast is a machine learning–based system designed to help farmers make better decisions by predicting future crop prices and giving simple farming advice. The system uses data such as past crop prices, weather reports, soil conditions, and market demand to make accurate predictions. Machine learning algorithms like Random Forest, LSTM, and XGBoost are used to analyze this data and suggest the best crops that can give higher profits. The main goal of AgriForecast is to support uneducated and rural farmers who may not have access to smartphones or the internet. Therefore, the system can also work through offline methods like IVR or SMS, where farmers can receive advice in their local language. This project helps farmers reduce risks, increase productivity, and make smart farming choices without depending on middlemen. Overall, AgriForecast helps improve farmers’ income, promotes sustainable agriculture, and shows how technology can support rural development in an easy and practical way.},
        keywords = {Machine Learning, Crop Price Prediction, Agriculture, Rural Farmers, Advisory System, LSTM, Random Forest, XGBoost, Sustainable Farming, IVR System, Smart Agriculture, Market Forecasting.},
        month = {November},
        }