Civil infrastructure systems experience damage, overloading, aging due to normal operations, severe environmental conditions, and extreme events. These effects change the structural behavior and performance. Novel structural health monitoring (SHM) strategies are increasingly becoming more important to objectively determine the actual condition and these changes. The main objective of this study is to demonstrate the integration of video images and sensor data as promising techniques for the safety of bridges in the context of SHM. The UCF 4-span bridge model is used to demonstrate the method. Image and sensing data are analyzed to obtain unit influence line (UIL) as an index for monitoring the bridge behavior under loading conditions identified using computer vision techniques. UILs are extracted for several different moving loads. In addition to the analysis of UILs in a comparative fashion, a new method based on statistical outlier detection from UIL vector sets is proposed and demonstrated. The new method is applied to detect and identify some of the most common damage scenarios for bridges such as changes in boundary conditions and loss of connectivity between composite sections. Successful results are obtained from the experimental studies.

The condition of civil infrastructure systems (CIS) changes over their life cycle for different reasons such as damage, overloading, severe environmental inputs, and ageing due normal continued use. The structural performance often decreases as a result of the change in condition. Objective condition assessment and performance evaluation are challenging activities since they require some type of monitoring to track the response over a period of time. In this paper, integrated use of video images and sensor data in the context of structural health monitoring is demonstrated as promising technologies for the safety of civil structures in general and bridges in particular. First, the challenges and possible solutions to using video images and computer vision techniques for structural health monitoring are presented. Then, the synchronized image and sensing data are analyzed to obtain unit influence line (UIL) as an index for monitoring bridge behavior under identified loading conditions. Subsequently, the UCF 4-span bridge model is used to demonstrate the integration and implementation of imaging devices and traditional sensing technology with UIL for evaluating and tracking the bridge behavior. It is shown that video images and computer vision techniques can be used to detect, classify and track different vehicles with synchronized sensor measurements to establish an input-output relationship to determine the normalized response of the bridge.

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Dr. Zaurin obtained his Bachelor Degree in Civil Engineering from 'Universidad de Oriente' in Venezuela in 1985. In 1990 he earned a MSc in Information Technology. He has been civil engineering professor with teaching experience at his Alma Mater (Universidad de Oriente) from 1986 until 2002. Dr. Zaurin moves to USA and completes another MSc, this time Structural and Geotechnical Engineering. Upon completing multidisciplinary PhD on Structural Health Monitoring Using Computer Vision, he joined UCF in 2010 as a Lecturer at the Civil, Environmental and Construction Engineering (CECE) Department. He has published computer vision related research work in prominent journals and still mentors graduate students in this particular area. Dr. Zaurin has been very active in the STEM area as he is one of the selected faculty members for the NSF funded EXCEL and NSF funded COMPASS programs at UCF. Dr. Zaurin received College Excellence in Undergraduate Teaching Award in 2015 and 2019, TIP Award in 2016, and also received 4 Golden Apple Awards for Undergraduate Teaching for a record four years in a row. During Fall 2013 he created IDEAS (Interdisciplinary Display for Engineering Analysis Statics) which is a project based learning activity designed specifically for promoting creativity, teamwork , and presentation skills for undergraduate sophomore and junior students, as well as by exposing the students to the fascinating world of scientific/technological research based engineering. IDEAS is becoming the cornerstone event for the sophomore engineering students at UCF: from fall 2013 to fall 2018 approximately 3000 students have created, designed, presented, and defended around 900 projects and papers.