Decision support system for integrating remote sensing in bridge condition assessment and preservation

摘要

Since the National Bridge Inventory (NBI) was first conducted, structural health monitoring (SHM) of U.S. bridgeinfrastructure has consisted largely of time and labor-intensive surveys with subjective results. In-situ and embeddedsensors, while more reliable and accurate, can be costly and in many cases infeasible for SHM because they requireinstallation in hard-to-reach places or during construction. Remote sensing (RS) technologies such as radar, electroopticalimaging and laser scanning may offer an innovative, cost-effective method of monitoring the dynamic conditionsof U.S. bridges in real-time. While some RS techniques may be costly for state agencies to deploy on their own, RSimagery is available through government agencies or commercial vendors for moderate or no cost. How can disparate RSdatasets be integrated with one another and with inventory data in a way that is meaningful to bridge asset managementdecision makers? This paper discusses the development and functionality of the Bridge Condition Decision SupportSystem (DSS), a web-based asset management tool for bridge managers and inspectors. The DSS seamlessly mergesbridge metrics from RS data with NBI inventory data allowing decision makers to compare up-to-date bridge conditionmetrics from multiple inputs as a time series. It enables analysis of RS and inventory data available through user-friendlyweb services which can also expose virtually unlimited server-side data processing. Using open-source software, theauthors developed a scalable, spatially-aware bridge condition database with a fast and flexible server applicationprogramming interface (API) and a cross-browser compatible web mapping application written in Javascript.© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.