Clustering and ontology-based information integration framework for surface subsidence risk mitigation in underground tunnels

Abstract

Building information modeling brings a fundamental technological innovation to the traditional architecture industry, which can optimize the construction process and improve the efficiency and effectiveness of the overall building process. Based on the information exchange of heterogeneous information systems and data around different stages of the whole life cycle of a building project, this article analyses the current state of building information interoperability and proposes an ontology-based information integration framework. In addition, hierarchical clustering method is used to analyze and find risk factors for surface subsidence in an underground tunnel construction project, and the results input into the information integration framework. The proposed approach maps the industry foundation classes data and relationships to an ontology, and utilizes an ontology-based reasoning model. An ontology for the underground tunnel has been developed using Protege and a Jena inference engine has been developed to investigate the early warning signs of ground subsidence.