- Condition detected from vehicle-mounted camera footage with machine learning
- Network-wide coverage at a fraction of the cost of instrumented surveys
- Results geo-referenced and loaded straight into the RAMS
- Repeatable every year, so deterioration trends become visible
- Feeds AI-assisted maintenance planning in the RAMS and BMS
The most expensive part of asset management is knowing the condition of the network, and the most common reason plans go stale is that the condition survey was done once, years ago. SirWay’s AI condition detection turns ordinary camera footage from a vehicle into geo-referenced condition data: surface defects are detected automatically, rated, and loaded into the Road Asset Management System.
Because the survey needs only a camera and a car, it can cover the whole network and be repeated every year. That is what makes deterioration trends visible, and what makes AI-assisted maintenance planning possible: a plan built on this year’s condition and last year’s, not on a survey from five years ago.
Where a decision needs measured data — roughness, bearing capacity, drainage — we combine AI detection with instrumented surveys, so the accuracy matches the decision rather than the other way round.