Lytx Technology Allows Driver Monitoring Without Recording Video

Drivers can use the app to review their performance. (Transport Topics)

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Video telematics company Lytx has introduced a new series of services ranging from improved driver monitoring to optional in-cab video recordings.

Underpinned by sensors that are placed in the cab, the company’s new so-named “Inattentive” algorithm uses machine learning and artificial intelligence to identify risky driver behavior, Lytx said during an Oct. 26 virtual media conference. The Risk Identification Without Recording configuration is another new service that allows fleets to monitor driver behavior without recording video.

“Lytx has been working for years on our state-of-the-art machine vision and artificial intelligence,” said Kristin Costas, product management director at Lytx. “Our latest algorithm, that we’re very excited to release, is what we’re calling Inattentive.”

Kristin Costas answers questions at the virtual event. (Transport Topics)

Costas said, “Inattentive is really detecting when the driver’s attention is not focused where it should be. This can take lots of different forms. Typically, we’re seeing drivers who are potentially rummaging through paperwork nearby. They might be looking at a cooler next to them. We also found this algorithm is able to detect instances when drivers are drowsy.”

Lytx has had algorithms available for more than a year that can detect when drivers are using handheld devices, not wearing their seat belts, eating food or smoking. Inattentive builds upon what the company learned from those versions with improved detection including speeding, inattentiveness, fatigue and drowsiness, along with capability for more fleet-specific customizations, it said. The technology is designed to help drivers be more proactive and accountable for their own improvement while providing management with real-time data on their behavior, Lytx said.

Sensors are placed in the cab. (Transport Topics)

Based on data collected from the sensors, the system uses the algorithm to alert the driver of risky behavior in real time while storing the data for review later. It is customizable so fleets can choose what types of behaviors they are alerted about. They also can still get real-time alerts and collect data without recording video.

“We’re really excited about this new algorithm and our ability to be able to detect general distractions that happen in the vehicle,” Costas said. “The other areas of risk that we’re focusing on is what’s happening on the road in front of the driver.”

Lytx already has been detecting outside conditions, such as following distance, critical distance, lane departure and rolling stop. Like the in-cab sensors, this technology leverages machine-learning algorithms. The new iteration adds speed monitoring to the mix of behavior monitoring.

(Transport Topics)

You can get into really granular details about when was the driver engaged in this behavior, exactly for how long,” Costas said. “Then the fleets have the ability and configuration of getting video of these behaviors. You can actually go in and browse and get video in real time.”

Lytx said it has the ability to detect more than 60 driving behaviors with greater than 95% accuracy. The technology will issue a real-time in-cab alert when an event is detected. The alert will include a light or spoken phrase, depending on the specific behavior.

“The second piece to this is what we call the driver check-in,” Costas said. “This is the ability of drivers to log in to our application either through our web application or driver app to watch their own videos and review their performance metric to see how their risks are changing over time.”

She added, “The real-time alerts are really focused on specific targeted behaviors that are intuitive and allow drivers to understand what they need to do to adjust,” Costas said. “There are a lot of configurations around those alerts.”

Lytx provides video telematics, analytics, safety and productivity solutions for commercial, public sector and field service fleets. Its services leverage machine-learning technology and span driver safety, risk detection, fleet tracking, compliance and fuel management.

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