Machine vision, AI, driving an evolution in fleet safety
Video event recorders and telematics platforms are advancing rapidly with machine vision and artificial intelligence (AI).
Early versions of the products — no more than a decade old by now — are limited in comparison to newer versions that use these technologies.
Lytx, a pioneer of video-based driver safety systems, recently shared with CCJ how it uses machine vision and AI to simplify the workflow for fleets while expanding the capabilities of safety and risk management.
About eight years ago, Lytx started down a path to use supervised and unsupervised machine learning in its DriveCam platform, explains Brandon Nixon, the company’s chief executive officer.
Machine learning starts onboard the vehicle with edge computing devices that detect “trigger” events. Algorithms in these devices constantly monitor streaming video and data from integrated cameras (machine vision) as well as from the vehicle databus and sensors.
Examples of basic trigger events include rapid deceleration and speeding. When these and more complex events occur, the devices capture and transmit video and data event files to servers in the cloud.