Mountain Rainfall Estimation and BIM Technology Site Safety Management Based on Internet of Things

Abstract

Mountain rainfall estimation is a major source of information for determining the safety of a geographical (mountainous) area. It can be done easily by using a modeling and simulation application, BIM, which is a building information modeling tool. It helps in transforming the real-time scenarios into the construction and business models. Now, this whole process can be easily realized by the help of an evolving technology known as IoT (Internet of Things). Internet of Things is supposedly going to take over the world by the end of this decade. It will reshape the whole communication architecture. IoT is actually going to be a basis for D2D (Device to Device) communication. Here, the MTC (Machine Type Communications) are going to take place which have almost zero human involvement. Now, in order to overcome the problem that the traditional construction site safety management method is difficult to accurately estimate the rainfall, resulting in poor safety management effect, a mountain rainfall estimation and BIM technology site safety management methods based on Internet of things are proposed. Firstly, based on the Internet of Things data, the limit learning machine method is used to accurately estimate the mountain rainfall. Secondly, based on the rainfall estimation results and combined with BIM technology, the construction site safety and management model is constructed. In the end, experimental verification is carried out. The experimental results show that this method can precisely estimate the rainfall in mountainous areas, and the computational results of safety factor are basically consistent with the actual results, indicating that the safety management effect of this system is good. In this paper, I reveal the complications and drawbacks associated with the ongoing mechanisms used for mountain rainfall estimations and how to overcome them by using the new technology, i.e., Internet of Things.