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Intelligent Monitoring System Based on Spatio–Temporal Data for Underground Space Infrastructure
Engineering ( IF 12.8 ) Pub Date : 2022-09-13 , DOI: 10.1016/j.eng.2022.07.016
Bowen Du , Junchen Ye , Hehua Zhu , Leilei Sun , Yanliang Du

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.



中文翻译:

基于时空数据的地下空间基础设施智能监测系统

基于时空大数据的智能感知、机理理解和劣化预测,不仅促进了基础设施的安全,而且为基础设施建设向智能化迈进提供了基础理论和关键技术。地下空间利用的推进,形成了深、大、集三个特征,形成了立体的城市布局。然而,与地上的建筑物和桥梁相比,地下发生的疾病和退化更加隐蔽且难以识别。在建设和服务期间仍然存在许多挑战。为了弥补这一差距,本文总结了现有的方法,并基于现实世界的空间安全管理评估了它们的长处和短处。

更新日期:2022-09-13
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