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@article{192951,
        author = {Aditi Jambhulkar and Sahil Ukey and Ruchita Barsagade and Roji Alam and Radhika Band and Dr. Pramod Gadge},
        title = {INTELLIGENT AGRICULTURAL PESTICIDE SPRINKLE SYSTEM},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {9},
        pages = {3661-3672},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=192951},
        abstract = {An intelligent agricultural pesticide sprinkler transforms contemporary crop management and protection by machine vision, IoT, and sophisticated robotics. The development of accurate, automated, and environmentally friendly pesticide and fertilizer application systems has been made possible by the quick development of technologies like deep learning, drone-based photography, and edge computing. These new systems employ image-based and sensor-driven real-time detection for precise pest, disease, and weed identification, allowing site-specific application and reducing environmental and health risks, in contrast to traditional manual spraying, which the World Health Organization links to over a million pesticide poisoning cases annually. Precision agriculture and autonomous sprayers, which employ machine learning algorithms like SVMs, CNNs, and transformer-based models to differentiate between crops and weeds, are becoming increasingly important, according to recent studies. This allows for the selective application of herbicides and reduces. Precision agriculture and autonomous sprayers, which leverage machine learning algorithms like SVMs, CNNs, and transformer-based models that distinguish between crops and weeds with the aim to promote selective herbicide application and reduce chemical waste, are becoming increasingly important, according to recent studies. Through remote sensing and intelligent data processing, UAV and robot-assisted technology further optimize resource utilization, providing quick, high-resolution weed mapping and field monitoring.
Innovations like the Smart Spray Analytical System and machine vision retrofit kits for tractors have demonstrated significant reductions in pesticide volume-often by 48–50% as well as enhanced spray pattern accuracy and drift management. These developments address persistent issues with labour shortages, environmental compliance, and the demand for high-quality products in spite of improving the sustainability and production of urban and traditional agriculture.Intelligent sprayers and economical agricultural robots can be customized for different field and orchard situations by integrating depth sensors, adaptive nozzles, and multi-modal imaging, as practical deployments illustrate. Together, these technologies permit autonomous, data-driven decision-making and ongoing field monitoring, boosting total production and supporting food security in the face of fast urbanization.},
        keywords = {precision agriculture, intelligent pesticide sprinkler, machine vision, IOT, deep learning, robotic farming.},
        month = {February},
        }