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Farm biosecurity hot spots prediction using big data analytics

In this paper a novel application of salad leaf disease detection has been developed using a combination of big data analytics and on field multi-dimensional sensing. Heterogeneous knowledge integration from publicly available various big data sources, calibrated with in-situ ground truth information, has the merit to be a very efficient way to tackle large area wise farm biosecurity related issues and early disease or pest infestation prevention. We propose a cloud computing based intelligent big data analysis platform to predict farm hot spots with high probability of potential biosecurity threats and early monitoring system aiming to save the farm from significant economic damage.