Design and application research of romote deformation management system of underground engineering surveying robot based on three-layer architecture information technology and deep learning algorithm

Abstract

The aim of this research study is to determine the Design and application research of a remote deformation management system of underground engineering surveying robot based on three-layer architecture information technology and deep learning algorithm. This research study is based on the primary data analysis conducted in Chinese organizations related to the engineering surveying robot and architecture information technology. For measuring, the research study used smart PLS software and run informative results, including R square, indicator correlations, discriminant validity, and composite reliability. The model fitness analysis also presents the smart PLS algorithm model for determining their relationship. The remote deformation management system is the main independent variable its included monitoring equipment and monitoring software are sub-parts of RDMS. The three-layer architecture information technology and deep learning algorithm are dependent variables. According to the overall research, the result found that the remote deformation management system of underground engineering surveying shows a positive and significant relation with deep learning algorithms and three-layer architecture information technology. The deep learning algorithm presents that direct link with remote deformation management systems; these remote systems play a vital role in an organization's development also workforce activities.