Fleets using artificial intelligence to accelerate safety, efficiency
As a form of AI, machine learning is making it possible to quickly find relevant patterns in data captured by Internet of Things (IoT) devices and sensors, explains Adam Kahn, vice president of fleets for Netradyne, which has a vision-based fleet safety system called Driveri (“driver eye”).
Ten years ago, fleet safety managers had to interpret critical events reported from telematics systems, Kahn says. A “hard brake” event, for instance, may not be a result of distracted or aggressive driving. The driver might have hit the brakes to avoid a car that suddenly him cut off in traffic.
Video-based safety systems give fleets context for hard braking and other safety-critical events. With machine learning, these systems have advanced to bring automation to the review process of video and data by identifying complex patterns of risk.