Towards sustainable infrastructure management: knowledge-based service-oriented computing framework for visual analytics

Rashna Vatcha; Seok-Won Lee; Ajeet Murty; William Tolone; Xiaoyu Wang; Wenwen Dou; Remco Chang; William Ribarsky; Wanqiu Liu; Shen-en Chen; Edd Hauser

doi:10.1117/12.819159

30 April 2009 Towards sustainable infrastructure management: knowledge-based service-oriented computing framework for visual analytics

Rashna Vatcha, Seok-Won Lee, Ajeet Murty, William Tolone, Xiaoyu Wang, Wenwen Dou, Remco Chang, William Ribarsky, Wanqiu Liu, Shen-en Chen, Edd Hauser

Author Affiliations +

Proceedings Volume 7346, Visual Analytics for Homeland Defense and Security; 734604 (2009) https://doi.org/10.1117/12.819159
Event: SPIE Defense, Security, and Sensing, 2009, Orlando, Florida, United States

Abstract

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 Integrated Remote Sensing and Visualization (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 events.

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Rashna Vatcha, Seok-Won Lee, Ajeet Murty, William Tolone, Xiaoyu Wang, Wenwen Dou, Remco Chang, William Ribarsky, Wanqiu Liu, Shen-en Chen, and Edd Hauser "Towards sustainable infrastructure management: knowledge-based service-oriented computing framework for visual analytics", Proc. SPIE 7346, Visual Analytics for Homeland Defense and Security, 734604 (30 April 2009); https://doi.org/10.1117/12.819159

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