Bahl Smart Bridge showcased as a Living Laboratory for Education and Research

This spring, students in Professor Bill Spencer’s CEE 573 Structural Dynamics II course were assigned a final project to utilize the Kavita and Lalit Bahl Smart Bridge and its instrumentation to develop modules that engage various audiences – including students, researchers and the general public – for the Grand Opening event and beyond. CEE 573 is designed to “provide an in-depth understanding of experimental and theoretical structural dynamics to enable students to work and conduct research in the field,” and this project is a key element of the class.  

The students formed five teams, with each team focusing on a different area, but all working to deepen their understanding of structural dynamics and achieve the ultimate project goal to “make the Smart Bridge a premier destination on campus.”

Some of the smart bridge features the students used during the course project include accelerometers that sense the motion of the bridge, displacement sensors at the expansion joints on the abutments, a pedestrian tracking camera and the high-precision data acquisition center.

“The smart bridge significantly enhances our ability to teach students how to leverage emerging technologies to monitor, understand and predict the behavior of structures, ultimately leading to safer and more resilient designs,” Spencer said. “The smart bridge will serve as a living laboratory for many generations to come – going far beyond our current capabilities and imagination. Such an experience is only available at Illinois.”

The students shared the results of their efforts during the grand opening event, introducing attendees to the features of the bridge through a special presentation and an interactive game they developed that challenged individuals to sneak across the bridge without the sensors detecting their footsteps. Summaries of the teams’ projects are described below.

 

Bridge Rock’n Roll’n
Mandy Zhong, Laurelin Strom, Ricardo Dorado

The students explored the capabilities of the bridge’s sensing system to learn about structural dynamics. Beginning with an initial computer-generated model, the team used measured data from the bridge to update the model to better represent the as-built structure. This “digital twin” of the bridge allowed students to simulate events and study the bridge response to various scenarios. In addition to the model’s education and research applications, the students proposed an interface that would engage the public: for example, by allowing bridge visitors to see how the bridge would react to a large earthquake.

 

Ninja Sneak Game
Travis Fillmore, Huy Tran

The students developed an interactive game called Ninja Sneak to engage the public and make the bridge a “must-see” destination for any trip to campus. The objective is to “sneak” across the bridge without the accelerometers detecting the impact of footsteps. Players can select the difficulty and the preferred time limit. A leaderboard will encourage visitors to keep coming back to the bridge to beat previous scores or keep a high score, and variations on the game allow for team play or increased difficulty. 

 

Computer Vision for Pedestrian Load Estimation and Tracking
Shaik Althaf V. Shajihan, Thomas Ngare Matiki, Ray Ausan

Using a camera installed on the bridge, the students showed how computer vision and machine learning can be used to turn sensor data from the smart bridge into useful data for the study of pedestrian traffic monitoring. After anonymizing the renderings (in this case, as stick figures), they track movements and load patterns. These methods can also be used for other research including vehicle monitoring, speed tracking and bridge statistics.

 

Smart Bridge Long Term Plans
Brian Welsh, Casey Rodgers

Building upon their successes, the students brainstormed ways to inspire researchers, students and the general public to further explore the bridge, both in-person and online. For example, users could manipulate 3D models of the bridge, helping them understand the real-time data; visitors could view informational topics or pick from a variety of mini-games to play, including the Ninja Sneak game described at left; and authorized users could access an online database of measured data for research and teaching purposes.  

 

CEE 573 Class Experience
Mohammad Fakhreddine, Alex Fields

During the course of the class, students delved heavily into data science and computer science to understand bridge behavior in response to external and internal stimuli. The students shared some of the lessons from the class, including good data collection practices, computer modeling, exploration of mode shapes (the movements of a structure – often invisible to the human eye – in reaction to forces acting on it), and model updating.

 

View a truncated version of the slideshow the students presented to guests: