How Edge AI is Turning Safety Managers into Strategists

AI has been integrated into the supply chain for quite some time.

- Pratik verma

It not only enhances efficiency but also improves quality. In this context, Netradyne is introducing fleet technology designed to support fleet growth and advocate for drivers.

Netradyne employs scientific methods and cutting-edge technology to statistically enhance driver performance and safety standards in transportation. Their vision-based edge AI is transforming traditional approaches to driver safety, road mapping, and the development of driving skills.

Speaking to Analytics Insight, Pratik Verma, Senior Director, Data Science, Netradyne, discusses how Netradyne's vision-based edge AI can fundamentally improve driver intelligence, fleet safety, and more.

Traditional fleet safety relies on telematics and rule-based alerts. How does visionbased edge AI fundamentally change the quality of driver intelligence?

For a long time, fleet safety has been built around hindsight. You review what happened and then try to prevent a repeat. But the real risk sits in the few seconds before impact, when human judgment is under pressure and milliseconds matter. That is why the shift from telematics to vision-based edge AI is fundamentally the move from knowing what happened to understanding why it happened. That “why” is the missing link in fleet safety, as the core distinction lies in causation.

Traditional telematics relies on abstracted signals, such as IMU patterns, G-forces, and braking intensity. If a driver slams on the brakes, a signal-based system flags a hard-braking event, but the signal alone cannot explain intent. Was the driver tailgating aggressively, or did a pedestrian suddenly step into the road and the driver made a strong defensive save? In a signal-only setup, both cases can look like a penalty or a violation.