Using Sensors and Robots to Better Manage Vulnerable Infrastructure
In June 2013, six train cars derailed when a bridge over Calgary’s Bow River failed due to the scouring of one of its piers in fast-moving flood waters. In February 2016, a major water main burst in Toronto, resulting in the flooding and a shutdown of the entire emergency department at St. Michael’s hospital.
These two seemingly unrelated incidents point to a common problem: the mechanisms behind catastrophic failures are often difficult to identify through visual inspections. In response, Dr. Sriram Narasimhan, Canada Research Chair in Smart Infrastructure, is developing state-of-the-art sensor platforms and novel decision-making tools to assess the state of vulnerable infrastructure that would otherwise be difficult to inspect.
His goal is to develop the mathematical framework, algorithms and software tools needed to automate the assessment of vulnerable infrastructure. The data required to inform the mathematical models will be obtained by developing new multi-sensor platforms, including robotic ground and water vehicles that can autonomously and reliably collect information where humans cannot.
In the long term, Narasimhan and his research team aim to develop the framework and tools needed to manage infrastructure as intelligent systems—that is, with embedded sensing, processing, actuation and communication capabilities and the capacity to autonomously learn and respond to hazards and interact with other intelligent systems, including humans.
Ultimately, Narasimhan’s research will lead to smart infrastructure that can be managed more cost-efficiently and will last longer and be less prone to catastrophic failure.