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@article{208849,
        author = {Pramith Rao and Rolvin Dsouza and Ranjith and Sadananda SS and Shruthi},
        title = {KrishiNethra-RRSP: An Integrated Smart Agriculture Platform Using AI, Deep Learning and IoT},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {4},
        pages = {3130-3135},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=208849},
        abstract = {Farmers often depend on separate sources for crop-health information, irrigation support, market-price updates, agri¬cultural equipment, government schemes, and selling opportunities. This fragmentation can increase the effort required to make timely decisions, especially when digital services are difficult to access or are not available in a preferred language. This paper presents KrishiNethra-RRSP, an integrated smart agriculture platform that combines artificial intelligence, machine learning, deep learning, and Internet of Things technologies with farmer-oriented digital services. The proposed platform includes image-based crop disease classification, IoT sensor integration for field monitoring and irrigation support, market and scheme information, equipment access, farmer-producer-organisation support, and multilingual voice assistance. The disease-classification component uses a Keras model with a 224 × 224 image input and twenty configured output classes covering black pepper, corn, rice, sugarcane, wheat, and an unknown category. The supplied model configuration records a test accuracy of 94.75% and uses a confidence threshold of
0.80. These values are reported as project-level records and are not treated as evidence of field performance. The paper describes the system architecture, implementation approach, available evaluation evidence, limitations, and future work required for reproducible and field-oriented validation.},
        keywords = {Smart agriculture, artificial intelligence, machine learning, deep learning, Internet of Things, crop disease detection, convolutional neural network, precision irrigation.},
        month = {September},
        }