Forecasting the Internet of Things Market by Using the Grey Prediction Model Based Forecast Method

Abstract

The Internet of Things (IOT), extensions of the Internet into everything in the real world, enables computation all over the world. Albeit important, very few studies intended to predict the IoT market. In order to forecast the IoT market effectively with very few data, the GM(1,1) based Grey forecasting model was introduced. Thus, the authors developed a GM (1,1) Grey system based pilot study for future short term wind power forecasting. The accurate predictions of the IoT market by using the GM(1,1) Grey forecasting method can serve as the basis for market analysis as well as strategic planning. An empirical study based on the real 2007-2011 worldwide IoT market data being provided by a leading market research institute has demonstrated the efficiency of the GM(1,1) based forecast mechanism. In the future, the GM(1,1) based forecast mechanism can further be applied to the forecast problems based on very limited time spans. Based on the forecast results, the IoT market will be over $700 billion in year 2020. The forecast error is 2.58%. The empirical study results being obtained in this research indicate that the proposed GM(1,1) based approach is a promising alternative for predicting the very short time series.