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@article{205620,
        author = {Prathmesh Mokashe and Rutvik Sawant and Suraj Bhujbal and Aditya Markad},
        title = {SMART AGRICULTURAL PREDICTION SYSTEM WITH MACHINE LEARNING},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {1},
        pages = {7386-7393},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=205620},
        abstract = {Agriculture is still the backbone of many economies in developing countries, but still, agricultural officers face issues such as unexpected climatic changes, soil erosion, agricultural diseases, and wastage of fertilizer. The traditional method of agricultural production largely depends on expertise and human decision-making, which may not always produce desired outcomes. This research work describes the development of a Smart Agricultural Prediction System using machine learning techniques and web development technologies for providing intelligent agricultural advisory support. The proposed system utilizes machine learning algorithms like Random Forest Regressor, Linear Regression, and classification algorithms for predicting the yield of crops, estimation of disease risk, analysis of weather, and recommendation of appropriate fertilizers considering the soil nutrition content and the type of crops. The proposed system has a Flask-based web application as the user interface. It provides a user-friendly interactive dashboard to the farmers and other stakeholders for real-time analysis and prediction results. The proposed system enables the integration of data preprocessing, feature development, and model development and the use of RESTful APIs for mobile platform integration. This project proves how AI and data analysis can improve the efficiency of precision farming and help minimize the loss of crops. This project solution can},
        keywords = {Smart Agriculture, Machine Learning, Crop Yield Prediction, Precision Farming, Flask, Data Analytics.},
        month = {June},
        }