From Risk to Efficiency : AI and Virtual Reality Redefine Bridge Checks
The Challenge of Keeping Bridges Safe
Bridges are the backbone of our infrastructure, but maintaining them is no small feat. In the UK, engineers inspect thousands of bridges every two to six years, often in tough conditions—think nighttime traffic or divers checking for scour underwater. These visual inspections (VI) are critical for spotting damage, but they’re costly, time-consuming, and sometimes risky. A new open-access paper, “A Review of Recent Research on Visual Inspection Processes for Bridges and the Potential Uses of AI,” by Vardanega et al., explores how technology could transform this process. Here’s what it means for the future of bridge management.
The State of Bridge Inspections Today
Visual inspections are the go-to method for assessing bridge health. Every two years, general inspections check for obvious issues, while detailed principal inspections happen every six years, often requiring inspectors to get up close. The data collected helps calculate Bridge Condition Indicators (BCIs), which track how bridges are aging across regions.
But there’s a catch:
Cost and Time: Inspections demand significant labor and financial resources.
Safety Risks: Inspectors work in harsh environments, and scour checks require divers, raising safety concerns.
Skill Gaps: The UK’s shortage of trained inspectors is a growing issue, despite efforts like the Bridge Inspector Certification Scheme.
A study of 200 UK bridges found that 81% of inspections strictly followed standards, with 93% meeting their intent. That’s solid, but the process is ripe for innovation, especially with advancements in AI visual inspection.
A Smarter Way : Offsite Inspections
What if we could move parts of the inspection process offsite? The paper highlights research into hybrid VI systems that use cutting-edge tech like:
Drones and 360° Cameras: Capture high-quality images without putting inspectors in harm’s way.
InSAR and Computer Vision: Detect structural changes remotely, from surface cracks to scour risks.
Virtual Reality: Allow offsite inspectors to “walk” through digital bridge models.
A proposed workflow (Nepomuceno et al., 2022) shows how remote inspections could work, slashing costs and risks. Early tests suggest offsite inspectors can reliably spot severe defects, though more data is needed to fully replace onsite visits. This shift aligns with emerging trends in AI infrastructure inspection, promising safer, faster inspections without sacrificing accuracy.
The AI Advantage
Artificial Intelligence (AI) is poised to take bridge inspections to the next level. The paper cites exciting advances:
Crack Detection: Deep learning models can pinpoint cracks with precision (Alexander et al., 2022).
Data Analysis: AI can sift through massive VI datasets to spot trends, helping managers prioritize maintenance across entire bridge networks.
Health Monitoring: Machine learning supports structural health monitoring, catching issues before they escalate (Munawar et al., 2022).
But AI isn’t a silver bullet. It struggles to assess defect severity as well as human inspectors, and its recommendations can be opaque. For example, if AI flags a defect for repair, will managers know why? Transparency is key to building trust in AI-driven decisions.
The Human Touch: Engineering Judgment
Here’s where things get interesting. The paper emphasizes that engineering judgment—honed by years of experience—is irreplaceable. Inspectors don’t just spot defects; they assess their impact and prioritize repairs based on context. AI can crunch numbers, but it’s the engineer who decides which bridge needs urgent attention. The challenge? Ensuring AI complements, not overrides, this expertise. Future systems must let managers safely question AI recommendations when they don’t align with on-the-ground realities.
What’s Next for Bridge Management?
The paper paints a hopeful picture:
Hybrid Inspections: Combining onsite and offsite methods for safer, more efficient VI.
AI-Powered Insights: Using AI to analyze VI data at scale, from regional trends to predictive maintenance.
Tech Integration: Drones, InSAR, and virtual reality becoming standard tools for inspectors.
But there’s work to do. We need more studies to validate offsite inspections and clearer guidelines for integrating AI without losing the human element. As the UK grapples with aging infrastructure, these innovations could extend bridge lifespans while saving time and money.
Join the Conversation
How can we balance technology and expertise in bridge management? Here’s how you can dive in:
Learn More: Read the full paper for free at Taylor & Francis to explore the research in depth.
Share Your Thoughts: What’s the biggest hurdle to adopting AI in inspections? Drop a comment below!
Explore Solutions: Interested in tech-driven bridge management? Connect with us to discuss drones, AI, and more. Message us.
The future of bridge inspections is bright—let’s build it together.
References
Vardanega, P.J., Tryfonas, T., Gavriel, G., Nepomuceno, D.T., Pregnolato, M., & Bennetts, J. (2024). A review of recent research on visual inspection processes for bridges and the potential uses of AI. In Bridge Maintenance, Safety, Management, Digitalization and Sustainability (pp. 3573–3580). Taylor & Francis. https://doi.org/10.1201/9781003483755-422
Alexander, Q.G., Hoskere, V., Narazaki, Y., Maxwell, A., & Spencer Jr, B.F. (2022). Fusion of thermal and RGB images for automated deep learning based crack detection in civil infrastructure. AI in Civil Engineering, 1(3). https://doi.org/10.1007/s43503-022-00002-y
Munawar, H.S., Hammad, A.W.A., Waller, S.T., & Islam, M.R. (2022). Modern crack detection for bridge infrastructure maintenance using machine learning. Human-Centric Intelligent Systems, 2(3-4), 95–112. https://doi.org/10.1007/s44230-022-00009-9
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