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@article{170091,
        author = {Hriday Badani and Dr S.T Patil and Aarya Gavaskar and Ahmad Ali Sayyed and Janhavi Awere},
        title = {Deep Learning Based Plant Disease Detection with a Farmer-Friendly Interface},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {6},
        pages = {3177-3184},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=170091},
        abstract = {The work temporarily drops metadata and instead focuses on a highly sophisticated model Convolutional Neural Network to predict potato leaf diseases. There are 3 categories of Potato leaves namly early blight, healthy and late blight , that PlantVillage dataset offers which is used for training the model. With the help of picture preprocessing methods, such as augmentation and rescaling allows better generalization to make precise diagnosis in different scenarios. Once a trained model has shown high accuracy during validation, it is provided to farmers using an API on Google Cloud where they can upload their images for disease prediction in real-time. This is then supplemented by a convenient user-friendly web interface which shows these predictions together with information regarding the detected condition, its etiology and potential therapies. The React, PHP-built web platform having MySQL and uses Leaflet for integration with HTML, CSS & JS. Using js for user location mapping, and Google Translate support to ensure that farmers are using the service in their native tongue. Apart from diagnosing diseases the platform also provides services like a blog, selling equipment and fertilizers, data-based insights about agricultural trends etc. In addition, the system stores disease outcomes and agricultural information of farmers in a MySQL database which can be used for further research on agriculture. Showcasing how deep learning and cloud technology driven by AI can disrupt precision agriculture through providing the marginal farming communities with access to them. Plant Pixel is intended to serve farmers as a comprehensive resource in addition to a disease detection tool. It provides opportunities for growth by forming alliances with governmental organizations, non-profits, and agricultural technology stakeholders.},
        keywords = {Potato leaf disease detection, Convolutional Neural Network, PlantVillage dataset, deep learning in agriculture, Google Cloud deployment, real-time disease prediction, multilingual farmer support, React web interface, precision agriculture, AI in farming, Leaflet.js mapping, agricultural research database, cloud-based disease detection, Plant Pixel platform, agricultural trends analysis.},
        month = {November},
        }