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@article{168739,
        author = {K PRASAD and B MURALI},
        title = {E-Agri Kit: Agricultural Aid Using Deep Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {5},
        pages = {1943-1948},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=168739},
        abstract = {This project presents an agricultural aid application, developed and designed, to help farmers by utilizing Image Processing, Machine Learning and Deep Learning concepts. Our application provides features such as early detection of plant disease, implemented using various approaches. After evaluation, results showed that Convolutional Neural Network was performing better for plant disease detection with an high accuracy. It further helps the farmer to forecast the weather to decide the right time for agricultural activities like harvesting and plucking. To avoid reoccurrence of disease due to loss in soil minerals, a crop specific fertilizer calculator is incorporated which can calculate the amount of urea, diammonium phosphate and muriate of potash required for a given area.},
        keywords = {Agricultural Aid Application, Plant Disease Detection, Image Processing, Machine Learning, Deep Learning, Convolutional Neural Network (CNN), Weather Forecasting, Fertilizer Calculator, Precision Agriculture Smart Farming},
        month = {October},
        }