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@article{186604,
        author = {sheetal misal and ms. shweta jarad and ms manisha mundhe},
        title = {AgriSmart: A Machine Learning-Based Smart Crop Recommendation System For Sustainable Agriculture},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {6},
        pages = {1671-1677},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=186604},
        abstract = {Sustainable agriculture demands innovative ap- proaches to optimize crop yield while minimizing resource usage and environmental impact. This paper presents AgriSmart, an intelligent, machine learning-based crop recommendation sys- tem specifically designed for Indian agricultural conditions. By leveraging Random Forest algorithms and enriched agronomic datasets, AgriSmart accurately predicts the most suitable crop based on key soil nutrients (N, P, K), pH, temperature, humidity, and rainfall. The system integrates a user-friendly, web-based interface equipped with interactive data visualizations, voice assistance, and chatbot support to deliver real-time, actionable insights to farmers with varying levels of digital literacy. Experi- mental evaluation demonstrates significant improvements in pre- diction accuracy over baseline models, reinforcing AgriSmart’s potential to enhance decision-making, increase crop productivity, and support sustainable farming practices across diverse agro- climatic zones in India.},
        keywords = {},
        month = {November},
        }