Researchers at the Massachusetts Institute of Technology (MIT) are developing software that measures automotive sounds and vibrations and communicates any service requirements and other diagnostic information to drivers via a smartphone.
To develop and evaluate the diagnostic systems, the team tested data from various cars, often renting the vehicles, creating conditions they wanted to be able to diagnose, and then reverting the autos to normal.
MIT researcher Joshua Siegel says many of the diagnostics stem from the use of machine-learning processes to compare numerous recordings of sounds and vibrations from well-tuned cars with similar vehicles that have a specific problem.
Siegel notes these systems can then filter out even highly subtle differences. For example, he says algorithms for identifying wheel balance problems are more accurate at detecting imbalances than expert drivers from a major automaker.
Siegel says a prototype smartphone app incorporating these diagnostic tools should be ready for field-testing in about six months.
From MIT News
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