A dynamic model for temperature prediction in glass greenhouse

As glass greenhouse becomes a main engine in smart agriculture, internet of things-based automation systems will enable control simply and efficiently for the greenhouse operation. However, a glass greenhouse operation strongly depends on the indoor temperature, humidity, and outside weather, the prediction of greenhouse temperature must consider the conditions. This work proposed a dynamic model by using the data of the sensors where they are distributed. By applying the relationship between inside temperature and humidity, and outside temperature. Our prototype model is not only process data in real-time but also improve the accuracy of indoor temperature prediction.