Factoring in frost for reliable insights even in unreliable weather

Our diagnostic approach to reliable insightsAt KONUX, we do not simply provide data, but we take a diagnostic approach to understanding the health of an asset, such as trackbed. For instance, if a sudden change is detected when the ballast is frozen due to low temperatures, our algorithms determine if a frost period is the likely reason for the change in data. The example below shows how our system has identified and flagged a frost period when the trackbed was frozen and we saw sudden changes in our data readings. Additionally, it shows that due to the temporary trackbed behaviour changes, prediction is suspended until the frost period has passed to not provide misleading readings or alerts. Frozen trackbed can have a temporary impact on our readings but importantly, is not related to the long-term health of the asset.