Predction disease using machine learning

Abstract

The economy of countries depends on agriculture to meet the needs of the population, achieve self-sufciency and export of peasant products to other countries, but there are some problems that threaten this sector, including fungal diseases and pests .These disease are mainly caused by weather and climate changes. In this work we investigate the usage of machine learning to predict these diseases and learn their relationship with the weather changes .Our work is apart of a large smart agriculture project that aims gathering dataset on agriculture using Internet of things . This dataset en composes many weather features and it is annotated manually by an expert on targeted diseases .we focus the deployed ML algorithm is Random forest and SVM. The generated models are achieved for disease prediction.