Design of Coffee Yield Estimation System Using Computer Vision by Crowd Counting Model

For coffee farmers, the yield of coffee is an issue that will affect their income. At present, the method used to estimate the coffee production is usually to estimate the production of the entire coffee garden by weighing the coffee till the harvest; however, this method does not have a way to understand the reasons of affecting coffee production in each period of the planting process. In this paper, we propose an intelligent system using a crowd counting model to estimate the yield of coffee, so that farmers can observe changes in the amount of coffee during the planting process from CCTVs remotely. Experimental results show that the proposed method can obtain estimated results with mean absolute error about 6.91.