The growth of RideView as a platform has closely mirrored the increasing maturity of video telematics in the North American market over the previous 5 years – from Wi-Fi dash cams that worked in conjunction with ELD tablets and smartphones that became prevalent with the introduction of the ELD mandate in late 2017, to standalone connected dual dash cams that work for fleets of any type today.

Video telematics is forecast to grow at a 16.6% CAGR in the North American region alone in the coming years (Berg’s Insight).

Video telematics, which started out as a niche application for enterprise fleets who could afford it, has now come fully of age.

In a not insignificant number of cases, commercial vehicles have accidents within a minute of leaving the yard - e.g., as quickly as the next STOP sign when a distracted driver ran through.

For someone who loves challenges, working on ML is a new challenge every day - no one day is the same as the other.

The value the fleets derive from video telematics takes many forms, though it is predominantly led by the need to have clear video evidence when crashes or other incidents occur, and increasingly with the advent of on-device AI, the ability to track, measure, and improve driver performance through real-time and offline coaching.

We have spoken before about the centrality of companion apps to the driver experience with a video telematics solution.

The advent of AI-based video telematics solutions has made real-time driver coaching possible.

Would you agree to drive a truck blindfolded for the length of an entire football field on a busy road?