Agronomy with IoT Devices: The Smart Solution for Detection of Diseases of Betel Leaves

The growth of the entire population in world and scarcity food crops are most challenging concept nowadays for solving these challenges, new mechanization like artificial intelligence, Internet Things mobile internet used this above-mentioned real- life problem. From 2019 onwards, a current perspective regarding Intelligent Agronomy has been focused on. For smart system, Thing (IoT) is column pillar because sensor devices being connected to perform various basic tasks. Different sensors irrigation system which based on controllers detectors vigilance water line, watering efficacy environment. Automatic leaf disease detection also very important monitoring other plant leaves with medicinal value. This detects symptoms automatically. In proposed decision- making authors have collected set betel images utilized image content characterization Support Vector Machine (SVM) classifier. stages initialization, bifurcation, eradication characteristics orderly arrangement involved processing mechanisms analyzing decisions. At time processing, an input rescaled as per requirement. Authors research paper eliminated color surface from sets classification training. will be able analyze test automatically decisions about whether it abnormal or good.