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@article{162074,
        author = {Rohit Anil Kumbhar and Prasad Sanjay Taware and Vishnukant Laxman Shinde and Avdhut Mohan Durgade and Ashwini  Bhapkar},
        title = {A Survey on : Agriculture Management System Using Web Development With Machine Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {7},
        pages = {345-347},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=162074},
        abstract = {Agriculture serves as the foundation of our nation, with a substantial percentage, ranging from 60-70%, relying directly or indirectly on it for sustenance in India. Being an agrarian-dependent country, India's progress is significantly intertwined with the agricultural sector. Despite its centrality, farming presents both advantages and drawbacks for Indian farmers. Our project endeavors to address these challenges by developing a web application that offers a reliable and beneficial platform for farmers to sell their produce. This initiative promises mutual profitability for both buyers and sellers. The application facilitates the online sale of pesticides and fertilizers, accompanied by instructional videos for the proper utilization of organic alternatives. Furthermore, the platform aids in the identification of plant diseases, offering remedies to minimize farm losses and enhance agricultural yields. Additionally, it serves as a unified platform for hiring farming workers, streamlining the labor procurement process for farmers.},
        keywords = {Agriculture, Worker, News, Image processing,
Random Forests.
},
        month = {},
        }