High-resolution monitoring of weather impacts on infrastructure networks using the internet of things

Two use-cases are presented for winter road maintenance and seasonal resilience on the railways to showcase the potentially transformative impact of the Internet of Things on observations and forecasting.

The impacts of weather and climate on infrastructure are numerous. For example, snow and ice on roads, railway buckling, leaves-on-the-line, wind impacts on power cabling etc. Advances in modelling mean that these impacts can now be predicted at a high resolution so that mitigation activities can be targeted at vulnerable sections of the infrastructure network.

However, whilst high-resolution models have been in operational use for the last decade, in an environment of increasing litigation, practitioners remain nervous about making mitigation decisions solely based on model output. This means that the verification of forecasts is now needed on a scale previously not required, and it is only with this step that end-users will become more open to using risk-based methods (e.g., decision support systems that enable selective salting for winter road maintenance where only the coldest sections of road are treated or localised rail speed restrictions in hot weather as opposed to the blanket restrictions currently used).

However, existing monitoring techniques are simply not capable of producing this information. Traditional, in-situ, measurements are too expensive to install in the numbers required and therefore lack the spatial resolution. Conversely, mobile measurements lack the temporal resolution to provide the full picture. This paper outlines how the emerging Internet of Things is starting to provide the enabling technology to saturate our infrastructure with low-cost sensors. In doing so, it will provide unprecedented monitoring of weather impacts as well as facilitating a new generation of products harnessing the benefits of high resolution observations.