Civil Infrastructure Systems Big Data Innovation Hub

Addressing the Problem

Currently $12.8 billion is invested annually in the construction and maintenance of bridges, while the annual amount needed to improve current bridge conditions is $20.5 billion. Big data analytics tools open unprecedented opportunities to significantly improve the effectiveness of decision-making with reduced cost by leveraging the large amount of data and information increasingly available in the CIS domain to generate useful actionable knowledge for improved decision-making. The use of Big Data analytics could transform the way civil infrastructure systems are operated and maintained so as to optimize decision making, improve safety, and reduce cost.

The goal of this project is to conduct seed transformative research and community network building activities at the nexus of Big Data and Civil Engineering towards establishing a Civil Infrastructure Systems (CIS) Big Data Innovation Hub at Illinois to accelerate scientific discovery that addresses the grand societal challenge of restoring and improving urban infrastructure.

Research Goals

  • Establish a Civil Infrastructure Systems (CIS)
  • Big Data infrastructure and repository at the University of Illinois at Urbana-Champaign;
  • Clarify the real-world needs in terms of data collection, integration, and analysis for supporting the operation and maintenance of the CIS;
  • Establish and foster the creation of a collaborative network that would grow to enable broad academic and industrial communities to collaborate for sustainable collection, management, and analysis of big data for supporting CIS decision-making; and,
  • Conduct seed transformative research in the area of semantic data/information search, mash-up, and analysis to explore how CIS big data analytics may improve the current methods and practices for transportation information systems—enhanced accessibility for transportation professionals to the right information, at the right time, and in an integrated manner, thereby resulting in more effective planning, design, operation, and maintenance decision-making.