Infrastructure management (and its associated processes) is complex to understand, perform and thus, hard to
make efficient and effective informed decisions. The management involves a multi-faceted operation that requires
the most robust data fusion, visualization and decision making. In order to protect and build sustainable critical
assets, we present our on-going multi-disciplinary large-scale project that establishes the <i>Integrated Remote Sensing
and Visualization</i> (IRSV) system with a focus on supporting bridge structure inspection and management.
This project involves specific expertise from civil engineers, computer scientists, geographers, and real-world
practitioners from industry, local and federal government agencies.
IRSV is being designed to accommodate the essential needs from the following aspects: 1) Better understanding
and enforcement of complex inspection process that can bridge the gap between evidence gathering
and decision making through the implementation of ontological knowledge engineering system; 2) Aggregation,
representation and fusion of complex multi-layered heterogeneous data (i.e. infrared imaging, aerial photos and
ground-mounted LIDAR etc.) with domain application knowledge to support machine understandable recommendation
system; 3) Robust visualization techniques with large-scale analytical and interactive visualizations
that support users' decision making; and 4) Integration of these needs through the flexible Service-oriented
Architecture (SOA) framework to compose and provide services on-demand.
IRSV is expected to serve as a management and data visualization tool for construction deliverable assurance
and infrastructure monitoring both periodically (annually, monthly, even daily if needed) as well as after extreme
Infrastructure safety affects millions of U.S citizens in many ways. Among all the infrastructures, the bridge
plays a significant role in providing substantial economy and public safety. Nearly 600,000 bridges across the
U.S are mandated to be inspected every twenty-four months. Although these inspections could generate great
amount of rich data for bridge engineers to make critical maintenance decisions, processing these data has become
challenging due to the low efficiency from those traditional bridge management systems. In collaboration with
North Carolina Department of Transportation (NCDOT) and other regional DOT collaborators, we present our
knowledge integrated visual analytics bridge management system. Our system aims to provide bridge engineers a
highly interactive data exploration environment as well as knowledge pools for corresponding bridge information.
By integrating the knowledge structure with visualization system, our system could provide comprehensive
understandings of the bridge assets and enables bridge engineers to investigate potential bridge safety issues and
make maintenance decisions.