ABSTRACT

Bridges across the U.S. continue to deteriorate at an alarming rate and the American Society of Civil Engineers estimate a cost of over $76 billion to improve the country's functionally obsolete or structurally deficient bridges. This indicates a significant demand for innovative bridge health monitoring solutions that can strategically guide management, maintenance and replacement programs without risking public safety. Unfortunately, the need to improve how our bridges are managed and repaired or replaced faces similar issues and demands as the rest of the U.S. transportation network: continuously shrinking resources and governing bodies who do not have the necessary insights from bridge health data to find a workable solution.

To discuss how to address these critical problems, researchers, practitioners, and individuals representing public and private sectors (transportation infrastructure and built environment owners, operators, designers and maintainers) convened with Big Data technology and analytics experts participated at the inaugural BRIDGE-ing Big Data Workshop hosted by the University of Nebraska in October 2015. During this workshop, it became clear that Big Data technology could assist with providing a timely solution. It also was apparent that past efforts focusing on utilizing bridge health monitoring and big data techniques as part of the management and maintenance/replacement processes are fragmented, and resulting datasets are not deemed trustworthy and are under-utilized. This project will (1) catalog datasets including sources, copyrights, license, collection procedures, and expected access controls from private sector, academia, and government agencies, (2) obtain commitments from stakeholders and host collaboration workshops with small working groups to discuss, import/export, and share bridge structural health monitoring data, and (3) solicit proposals from businesses/researchers to develop innovative applications that integrate disparate and voluminous data sources. It is anticipated that this project's findings will benefit the Midwest Big Data Hub transportation spoke and potentially inform similar activities for highways, buildings, power distribution networks and other civil infrastructure entities. Findings from this project will be promoted to national and international technical organizations, to directly impact workforce development, education and research programs. Combined, this project will make a direct impact on our country's ability to efficiently maintain the health and safety of its bridges.

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