The current approach to corrosion severity prediction is to use long-term averages of environmental parameters (such as relative humidity, temperature, and pollutants), geographic features (such as coastal proximity), and witness coupon corrosion rates of indicator materials to classify an environment into one of a small number of severity categories. However, recent work has revealed that brief changes in environmental conditions—even those lasting only a few hours—can significantly affect total corrosion damage, and long-term averages of environmental conditions are not sufficient to accurately predict cumulative corrosion damage. To more accurately measure the corrosion damage from these short-term events, corrosion sensors are becoming increasingly popular.  The frequent acquisition of data and increased measurement sensitivity are attractive features, however the data from these corrosion sensors is still difficult to interpret in many cases.