Abstract: Agriculture stands as a cornerstone in meeting the escalating demands of a burgeoning global population for sustenance. However, traditional methodologies for detecting diseases and administering pesticides to crops are riddled with inefficiencies, being both labor-intensive and time-consuming. To address these formidable challenges, we present a novel endeavor: the refinement of a Machine Learning Based Pest Recognition and Pesticide Sprayer system. This innovative project aims to revolutionize agricultural practices by automating the tasks of pesticide application and disease detection through the integration of cutting-edge IoT and artificial intelligence technologies.

| DOI: 10.17148/IARJSET.2024.11473