Intelligent Monitoring System Based on Spatio–Temporal Data for Underground Space Infrastructure

• DOI: 10.1016/j.eng.2022.07.016
• Publication Date: 2022-09-13T07:08:04Z
• Authors: Bowen Du; Junchen Ye; Hehua Zhu; Leilei Sun; Yanliang Du
• Keywords: Machine learning; Spatio–temporal data; Underground space infrastructure; 0211 other engineering and technologies; 02 engineering and technology; TA1-2040; Engineering (General). Civil engineering (General); Structure health monitoring

Intelligent sensing, mechanism understanding, and the deterioration forecasting based on spatio–temporal big data not only promote the safety of the infrastructure but also indicate the basic theory and key technology for the infrastructure construction to turn to intelligentization. The advancement of underground space utilization has led to the development of three characteristics (deep, big, and clustered) that help shape a tridimensional urban layout. However, compared to buildings and bridges overground, the diseases and degradation that occur underground are more insidious and difficult to identify. Numerous challenges during the construction and service periods remain. To address this gap, this paper summarizes the existing methods and evaluates their strong points and weak points based on real-world space safety management. The key scientific issues, as well as solutions, are discussed in a unified intelligent monitoring system.