Researchers say they have developed an algorithm that can be run against a variety of systems including cars, power plants, satellites and networks that would let users spot and fix problems faster.
In theory the technique, known as the Intelligent Outlier Detection Algorithm, or IODA could let operators keep a system performing even while it's failing, Andrew Weekley, a software engineer at the National Center for Atmospheric Research (NCAR) who led the algorithm development effort stated in a release. "When a system starts to fail, it's absolutely critical to be able to control it as long as possible. That can make the difference between disaster or not."
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According to researchers, if sensors malfunction and begin transmitting bad data, computers programmed with IODA could spot the problem and isolate bad data. The algorithm, researchers say, is an expert system that uses statistics, graph theory, image processing and decision trees, can be applied in cases where the correct assessment of data is critical, the incoming data are too numerous for a human to easily review, or the consequences of a sensor failure would be significant, researchers stated. IODA typically works by evaluating data from sensor systems and treating them as "images" that mimics the way a person might look at a plot of data points to spot an inconsistency, researchers said.
To find bad data, complex operations typically rely on multiple sensors, as well as algorithms that characterize specific relationships among the data being collected, and identify failures when the data unexpectedly change, researchers stated.
A drawback in most of those methods is they are designed for a particular type of time series and can fail catastrophically when applied to different types of data, especially in situations where there are numerous and sometimes subtle errors, experts said.
The algorithm consists of several thousand lines of a technical computing language known as MATLAB. Developers may expand and translate it into a computer programming language such as C so it can be used for commercial purposes, researchers said.
This is not the first use of Outlier algorithms. Other examples of its use can be found in data mining applications for example.
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