A Cloud-IOT Based Decision Support System for Potato Pest Prevention

Abstract

Adopting decision support system (DSS) in farming to prevent potato late blight disease has proven its utility. As a matter of fact, the DSS grants efficiency, and reduces production cost as well as the impact on the environment as that it estimates the exact amount of fungicide that must be applied. This estimation uses environmental condition-based blight forecast model. Usually requires weather information collected from costly weather stations or imprecise historical data. However, climate data could be collected easily thanks to the evolution of the Internet of Things (IOT). In fact, this could be done by deploying a large number of low-cost, low-power sensor nodes inside farms. Climate data can be routed afterwards from the sensors to the Cloud-IOT framework through an internet connection. In this paper, we developed and experimented Cloud-IOT based late blight decision support system. In comparison with to the state of art DSS, report our proposed system offers wider accessibility and a cheaper cost.