A scalable offline AI-based solution to assist the diseases and plague detection in agriculture

Abstract

Early detection of diseases and pests is a key factor in eradicating or minimizing the damage that {these} may cause.In this work, a comprehensive solution is presented that is based on the compositing of existing cloud solutions and mobile tools to detect in-situ issues.The platform presented was used for the detection of powdery mildew and Cladosporium diseases in tomatoes.The results of using the approach to carry out this task were more than satisfactory since it managed to correctly detect the symptoms, having mAP of 0.41 in at least some of these symptoms. We analyzed the performance of our dataset on the one hand and the combination of PlantDoc dataset on the other hand. This shows that the platform can be used in the agriculture sector, as an additional tool for detecting diseases and pests in order to combat the problem and reduce its consequences.