Faster computers and smarter algorithms mean the ability to crunch more data than ever.
Ron Bisio, senior vice president of Trimble’s Transportation sector, recently discussed predictive maintenance as part of a larger discussion of artificial intelligence during Trimble’s Insight conference.
“We’re coming up with a single source of truth on maintenance activities, and that’s going to be really, really important for future predictive maintenance,” he explained.
Artificial intelligence operates by having a lot of data to work with. Predictive maintenance systems are bringing in not only the fleet’s data, but also data from other sources, including aggregated data from other customers of providers.
For instance, Aperia said it has more than 1 million tires under management, which expands the learning capabilities of its Halo Connect and Halo Trailer Connect platforms, which use machine learning to
“The algorithms powering the solution will only get smarter, multiplying the value delivered to fleets with every rotation of the wheel,” said Judith Monte, vice president of marketing and customer success at Aperia.
One challenge with AI is the old IT saying of “garbage in, garbage out,” explained Trimble CEO Rob Painter. “The data quality matters enormously, and that’s why we work so hard in our world to make sure the data flows across that supply chain. That is easy to say — and hard to do.”
Allowing access to all this data also means you need to think about protecting it, says Jean-Sébastien Bouchard, executive vice president of sales and a co-founder of Isaac Instruments. He says it’s best to think of your telematics provider as a “pipeline” between your trucks and your fleet managers.
Moreover, he suggests talking with providers and making sure that they will never share or monetize your data.
“Be absolutely certain your provider understands and agrees — in writing — that any data collected (and any copies of it) belongs solely to your fleet,” he says.