Case Study: Pitstop
Roadside breakdowns are a common and expensive annoyance for motorists the world over. In 2015, there were 35 million of them in the U.S. alone. Currently, there’s no readily accessible way to determine if a vehicle’s components are nearing malfunction-failure stage. The results: missed meetings, family vacation disasters, and expensive towing-repair charges: we’ll all been there.
Is there a better way: a solution? Yes, now there is – and it’s AI-driven.
Pitstop is a Toronto, Canada-based AI company that’s engineered a way to eliminate roadside breakdowns by proactive, predictive computation and real-time communications.
Their tech involves:
Mobile app, telematics device and artificial intelligence
How it works:
An on-board AI data engine integrates incoming data from 300 sensors within a vehicle and combines it with:
- Aggregate info compiled from supply chain
- Dealership service records over past 10 years
- Auto manufacturers’ component servicing recommendations
Adherence to emissions standards confirmed, component failure predicted and maintenance needs identified. Flagged items communicated in real-time to the dealership and vehicle serviced before disaster strikes.
This video provides an explanation of how machines learn and develop artificial intelligence.