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.
Highlights
Rainfall is an important parameter of mountain construction, which largely reflects the trend of disasters
Represents the input vector of safety status monitoring on the construction site, wj represents the initial value given to the weight vector, M represents the number of neurons in the output layer, and Euclidean distance is used as the discrimination function of competition; based on the physical quantity value of the construction site safety monitoring information node obtained by the above formula, the following formula is used to represent the competition rules of the construction site safety monitoring data information node:
In order to verify the practical application performance of the proposed mountain rainfall estimation based on the Internet of ings and the field safety management method of BIM technology, comparative verification experiments are carried out
Summary
Rainfall is an important parameter of mountain construction, which largely reflects the trend of disasters. Represents the input vector of safety status monitoring on the construction site, wj represents the initial value given to the weight vector, M represents the number of neurons in the output layer, and Euclidean distance is used as the discrimination function of competition; based on the physical quantity value of the construction site safety monitoring information node obtained by the above formula, the following formula is used to represent the competition rules of the construction site safety monitoring data information node: P′. It can be stated that, by fusing the distance mapping method to obtain the phase velocity of the construction site safety monitoring information, the competitive layer neuron, and its input mode weight vector, mapping the dimension reduction of the input vector to the two-dimensional flat key, and the construction site safety supervision can be effectively completed
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