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@article{178944,
        author = {Shubham Kumar and Braham Kumar Sah and Bikash Kumar Singh and Shiv Kumar Yadav and Dr. Malatesh S H},
        title = {IOT Device for Detecting Leaves Diseases in Plants by Image Processing},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {6034-6039},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=178944},
        abstract = {The rapid growth of the Internet of Things (IoT) has enabled the development of smart agricultural solutions to improve crop health monitoring and disease management. This project proposes an IoT based system for early detection of plant leaf diseases using Convolutional Neural Networks (CNNs). The system captures leaf images through a camera-equipped IoT device, processes the images locally, and applies a trained CNN model to classify and identify potential diseases. By automating the detection process, farmers can receive real-time alerts and recommendations, reducing crop loss and improving productivity. The proposed solution integrates lightweight CNN architectures optimized for IoT deployment, ensuring high accuracy with minimal computational resources. A user-friendly interface allows farmers to monitor plant health remotely. This system not only enhances decision-making but also promotes sustainable farming practices by enabling targeted use of pesticides and fertilizers.},
        keywords = {IoT, Raspberry Pi, Image Processing, Plant Leaf Disease Detection, Smart Agriculture, Machine Learning, Disease Classification, Precision Farming.},
        month = {May},
        }