Bridge health monitoring dashboard
Inspired by publicly reported work at Arup
Combine crack detection from photos with sensor anomaly alerts into a monitoring dashboard for bridge engineers.
The brief
Arup has described a cloud-based structural health monitoring service on the Galecopper bridge, where sensor data is stored, processed and interpreted by bridge engineers to make decisions. Build a monitoring product of your own: detect cracks in concrete photos, simulate bridge sensor streams and flag anomalies in them, and bring both into a dashboard that tells an engineer what to inspect first. Good looks like: crack detection accuracy, an anomaly detector judged on injected faults, a ranked inspection list, and a written design for sensors and data flow.
Read the case first
What Arup has said in public about this kind of work, on its own pages:
Make it your own
Monitor a structure near you: a flyover, a foot overbridge or your college building. Photograph it (from public places), place imaginary sensors where an engineer would, and explain why.
AITeky has no link with Arup, which has not reviewed or endorsed this brief. The brief only draws on what the company has published, uses open data rather than its data, and is a learning exercise: don't present your project as Arup's work or system.
What you will build
- Train a crack classifier or segmenter on concrete images
- Simulate strain, vibration and temperature sensor streams
- Detect anomalies and injected faults in the streams
- Rank elements for inspection from both sources
- Build an engineer dashboard
- Write the sensor and data-flow design
Free, open data to build it with
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