A scalable cloud-based cyberinfrastructure platform for bridge monitoring

Cloud computing is a computing paradigm wherein computing resources, such as servers, storage and applications, can be provisioned and accessed in real time via advanced communication networks. In the era of Internet of Things (IoT) and big data, cloud computing has been widely developed in many industrial applications involving large volume of data. Appropriate use of cloud computing infrastructure can enhance the long-term deployment of a structural health monitoring (SHM) system which would incur significant amount of data of different types. This paper presents a cloud-based cyberinfrastructure platform designed to support bridge monitoring. The cyberinfrastructure platform enables scalable management of SHM data and facilitates effective information sharing and data utilisation. A cloud-based platform comprises of virtual machines, distributed database and web servers. The peer-to-peer distributed database architecture provides a scalable and fault-tolerant data management system. Platform-neutral web services designed in compliant with the Representational State Transfer (REST) standard enables easy access to the cloud resources and SHM data. For data interoperability, a bridge information model for bridge monitoring applications is adopted. For demonstration, the scalable cloud-based platform is implemented for the monitoring of bridges along the I-275 corridor in the State of Michigan. The results show that the cloud-based cyberinfrastructure platform can effectively manage the sensor data and bridge information and facilitate efficient access of the data as well as the bridge monitoring software services.

  • Record URL:
  • Availability:
  • Supplemental Notes:
    • © 2018 Informa UK Limited, trading as Taylor & Francis Group. Abstract republished with permission of Taylor & Francis.
  • Authors:
    • Jeong, Seongwoon
    • Hou, Rui
    • Lynch, Jerome P
    • Sohn, Hoon
    • Law, Kincho H
  • Publication Date: 2019-1

Language

  • English

Media Info

Subject/Index Terms

Filing Info

  • Accession Number: 01691642
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Jan 16 2019 3:01PM